CN109917758A - A kind of processing method and system of industrial equipment data - Google Patents
A kind of processing method and system of industrial equipment data Download PDFInfo
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Abstract
The invention discloses the processing methods and system of a kind of industrial equipment data, the device data of industrial equipment is acquired by sensor, and the device data is sent to corresponding gateway, the device data received is sent to wireless sensor network server by each gateway, wireless sensor network server calculates the device data received according to trained obtained machine learning model, predict the health information of corresponding industrial equipment, and corresponding health information is sent to Distributed Storage platform and is stored, the health information that data display platform is stored according to Distributed Storage platform shows the health status of the industrial equipment of prediction, scheme disclosed by the invention takes full advantage of technology of Internet of things, big data technology and machine learning techniques, device data based on sensor acquisition It is predicted, improves the use value of data, keep the management of factory more intelligent, reduce the investment of human resources.
Description
Technical field
The present invention relates to internet of things field, a kind of processing method more specifically to industrial equipment data and
System.
Background technique
With the fast development of information technology and automatic technology, the integrated level and complexity of modern industry system are increasingly
Height is had outstanding performance in fields such as Aeronautics and Astronautics, communication, semiconductor, high-speed rail transportation, metallurgy and chemical industry.Due to man-made system
Integral link be continuously increased, influencing each other between each section also becomes increasingly complex, and system jam and function is caused to be lost
The probability of effect is gradually increased.With the promotion required system reliability, fault detection, diagnosis and Predicting Technique are by academia
And the extensive concern of industry.
In " National Program for Medium-to Long-term Scientific and Technological Development 2006-2020 ", " great product and great installation
Forecasting technique in life span " is proposed as cutting edge technology.Equipment fault prognostics and health management technology (PHM) has become one and covers
The multi-field cross discipline and research hot topic such as basic material, mechanical structure, the energy, electronics, automatic test, reliability, information
Direction has important application value and realistic meaning.
In existing industrial circle, be usually all periodically industrial equipment is checked by maintenance personnel so that it is determined that
The health status of industrial equipment, this mode not only waste of manpower resource for determining industrial equipment health status, but also not enough
It is intelligent.
Summary of the invention
In order to solve the above technical problems, the present invention provides the processing method and system of a kind of industrial equipment data.
To achieve the above object, specific technical solution of the present invention is as follows:
A kind of processing method of industrial equipment data, comprising:
S1: the device data of each sensor acquisition industrial equipment, and the device data is sent to corresponding gateway and is set
It is standby；
S2: the device data received is sent to wireless sensor network server by each gateway；
S3: the wireless sensor network server is according to trained obtained machine learning model to described in receiving
Device data is calculated, and predicts the health information of corresponding industrial equipment, and corresponding health information is sent to
Distributed Storage platform is stored；
S4: the health information that data display platform is stored according to the Distributed Storage platform is by the work of prediction
The health status of industry equipment is shown.
Further, the device data includes in equipment electricity consumption data, device temperature data and equipment humidity data
At least one.
Further, after the S2, further includes:
The wireless sensor network server parse and will obtain after parsing to the device data received
Data be sent to the Distributed Storage platform and stored.
Further, the S3 includes:
S30: the data flow length for the device data that the wireless sensor network server statistics receives；
S32: when determining that data flow length to be processed reaches pre-set length threshold, according to trained obtained engineering
Practise model the device data is calculated, predict corresponding industrial equipment in the preset time period after current time whether
It will appear failure.
Further, the S3 includes:
S31: when the wireless sensor network server starts to start timer when receiving the device data；
S33: to the device data received in the prefixed time interval according to trained after prefixed time interval arrival
Obtained machine learning model is calculated, predict corresponding industrial equipment in the preset time period after current time whether
It will appear failure, and timer reset, restart timing.
Further, the data display platform includes WEB server and display terminal, and the S4 includes:
S41: the WEB server receives the health information that the Distributed Storage platform is sent, and by institute
It states health information and is sent to the display terminal logged in the WEB server；
S42: the display terminal shows the health information received.
Further, the S4 includes:
The health information that the data display platform is stored according to the Distributed Storage platform is by prediction
The health status of industrial equipment is shown by icon and/or report and/or text.
The present invention also provides a kind of processing systems of industrial equipment data, comprising: sensor, gateway, wireless sensing
Device network server, Distributed Storage platform and data display platform；
The sensor is used to acquire the device data of industrial equipment, and the device data is sent to corresponding gateway
Equipment；
The gateway is used to the device data received being sent to wireless sensor network server；
The wireless sensor network server is used for according to trained obtained machine learning model to the institute received
It states device data to be calculated, predicts the health information of corresponding industrial equipment, and corresponding health information is sent
It is stored to the Distributed Storage platform；
The data display platform is used for will be pre- according to the health information that the Distributed Storage platform stores
The health status of the industrial equipment of survey is shown.
Further, the wireless sensor network server is also used to parse the device data received
And data obtained after parsing are sent to the Distributed Storage platform and are stored.
Further, data flow of the wireless sensor network server for counting the device data received is long
Degree, when determining that data flow length to be processed reaches pre-set length threshold, according to trained obtained machine learning model pair
The device data is calculated, and predicts whether corresponding industrial equipment will appear event in the preset time period after current time
Barrier；Or the wireless sensor network server for start when receiving the device data start timer when,
To the device data received in the prefixed time interval according to trained obtained machine learning after prefixed time interval arrival
Model is calculated, and predicts whether corresponding industrial equipment will appear failure in the preset time period after current time, and
Timer is reset, timing is restarted.
The processing method and system of industrial equipment data provided by the invention, the equipment that industrial equipment is acquired by sensor
Data, and the device data is sent to corresponding gateway, the device data received is sent to nothing by each gateway
Line sensor network server, wireless sensor network server is according to trained obtained machine learning model to receiving
Device data is calculated, and predicts the health information of corresponding industrial equipment, and corresponding health information is sent to
Distributed Storage platform is stored, and data display platform is believed according to the health status that Distributed Storage platform stores
Breath shows the health status of the industrial equipment of prediction, and scheme provided by the invention takes full advantage of technology of Internet of things, big
Data technique and machine learning techniques, the device data based on sensor acquisition is predicted, improves the use value of data,
Keep the management of factory more intelligent, reduces the investment of human resources.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is the flow diagram of the processing method of industrial equipment data provided in an embodiment of the present invention；
Fig. 2 is the protocol frame schematic diagram of method provided in an embodiment of the present invention；
Fig. 3 is that data move towards schematic diagram in method provided in an embodiment of the present invention；
Fig. 4 is the healthy shape that wireless sensor network server predicts industrial equipment in method provided in an embodiment of the present invention
The first pass schematic diagram of condition；
Fig. 5 is the healthy shape that wireless sensor network server predicts industrial equipment in method provided in an embodiment of the present invention
The second procedure schematic diagram of condition；
Fig. 6 is a kind of system structure diagram provided in an embodiment of the present invention；
Fig. 7 is the process signal for the health status that data display platform provided in an embodiment of the present invention shows industrial equipment
Figure；
Fig. 8 is the structural schematic diagram of the processing system of industrial equipment data provided in an embodiment of the present invention.
Specific embodiment
In order to keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and
Specific embodiment is described in detail, it should be understood that the specific embodiments described herein are merely illustrative of the present invention, not
For limiting the present invention.
Cause usually periodically check to the health status of industrial equipment by maintenance personnel in the existing technology of solution
The problem of waste of human resource, not smart enoughization, the present embodiment provides a kind of processing method of industrial equipment data, the present embodiment
The open source component and machine learning algorithm that the method for offer has used reliable big data storage to calculate, are not only able to set industry
Data in large scale and changeable are acquired storage in standby, additionally it is possible to using data to equipment state progress modeling analysis and in advance
It surveys, improves the usable value of data, so that the management of factory is more intelligent, be effectively utilized technology of Internet of things, machine learning
The technology of technology and big data is transformed traditional industry, and the processing method of industrial equipment data provided in this embodiment can
With shown in Figure 1, comprising:
S1: the device data of each sensor acquisition industrial equipment, and device data is sent to corresponding gateway.
Each of the present embodiment needs that one or more can be arranged on the industrial equipment for carrying out health monitoring
Sensor, or sensor, the device data in the present embodiment can be set in the direct environment locating for corresponding industrial equipment
The data that can characterize the industrial equipment current state can be arbitrary, including but is not limited to is equipment electricity consumption data, equipment
At least one of temperature data, equipment humidity data and the relevant data of equipment work.
S2: the device data received is sent to wireless sensor network server by each gateway.
S3: wireless sensor network server is according to trained obtained machine learning model to the device data received
Analytical calculation is carried out, predicts the health information of corresponding industrial equipment, and corresponding health information is sent to distribution
Formula data storing platform is stored.
Distributed Storage platform in the present embodiment is substantially a big data platform, can store a large amount of number
According to.
S4: the health information that data display platform is stored according to Distributed Storage platform sets the industry of prediction
Standby health status is shown.
The health information that data display platform in the present embodiment can be stored according to Distributed Storage platform
The health status of the industrial equipment of prediction is shown by icon and/or report and/or text, for example, can will be every
The time of the failure of specific failure and appearance that one industrial equipment is likely to occur all shows, in order to equipment management personnel
It is ready in advance.
It should be noted that in order to be managed to multiple industrial equipments, each industrial equipment should have it is corresponding only
One identification badge, sensor can bind the device data of acquisition with the identification badge of corresponding acquisition target
To send jointly to gateway, and wireless sensor network server, wireless sensor network are sent jointly to by gateway
Network server can predict corresponding health information according to device data, and by the health information with it is corresponding
Identification badge binding is got up, and such data display platform can be by the health status of each industrial equipment and corresponding work
Industry equipment is shown, and administrative staff can get the healthy shape of each industrial equipment by inquiring data display platform
Condition.
In some embodiments, upon step s 2, can with the following steps are included:
Wireless sensor network server parse and send out data obtained after parsing to the device data received
It send to Distributed Storage platform and is stored.
In this way, wireless sensor network server can get the historical equipment data of industrial equipment at any time, more
Maintenance, monitoring convenient for equipment, it should be noted that when having multiple industrial equipments in application environment, the number that stores here
According to should also be as carrying out binding storage with the identification badge of industrial equipment.
Method provided by embodiment can use protocol frame shown in Fig. 2, including data acquisition and transport layer, data
Accumulation layer, data, which are calculated, acquires the function with transport layer mainly by sensor and net with analysis layer and data application layer, data
It closes equipment to realize, specifically, each sensor can acquire device data, data storage layer is then transmitted to by gateway,
Data storage layer in the present embodiment is corresponding with Distributed Storage platform namely Distributed Storage platform includes
Hadoop cluster, ElasticSearch cluster, distributed caching and relational data warehouse, gateway can pass through
Unstructured data in data that sensor acquires is transmitted to Hadoop cluster and stored by Secure File Transfer Protocol, and others are set
Standby data can then be stored being transmitted to ElasticSearch cluster after parsing or training and calculate, specifically,
Gateway can use MQTT agreement that device data is sent to wireless sensor network server in a manner of queue, wirelessly
Sensor network server is analyzed the data flow (namely stream data in Fig. 3) received, is parsed, this process
It is the process of stream data analysis, in addition, wireless sensor network server can also be every according to the device data received
The regular threshold value of primary strategy is just calculated every a preset time interval, prefixed time interval here should be sufficiently small, thus
Reach real-time effect, then can when the length of obtained satisfactory stream data reaches pre-set length threshold according to
The regular threshold value of strategy being currently calculated and pre-set training pattern are calculated, satisfactory streaming here
Data can refer to the data by wireless sensor network server dissection process, this process and off-line data point in Fig. 2
The process of analysis is corresponding, predicts the health status of industrial equipment, and prediction result is then transmitted to ElasticSearch cluster and is carried out
Storage, in this process, the threshold value and decision being calculated in real time can also transmit ElasticSearch cluster and be deposited
Storage, it should be noted that gateway can be encrypted when being carried out the transmission of data using MQTT using SSL, with
Guarantee the safety of data transmission, the trend of data may refer to shown in Fig. 3 in the present embodiment corresponding with Fig. 2.
Shown in Figure 4, in a kind of example, step S3 may include following sub-step:
S30: the data flow length for the device data that wireless sensor network server statistics receives.
S32: when determining that data flow length to be processed reaches pre-set length threshold, according to trained obtained engineering
Practise model the device data is calculated, predict corresponding industrial equipment in the preset time period after current time whether
It will appear failure.
Shown in Figure 5 in another example, step S3 may include following sub-step:
S31: when wireless sensor network server starts to start timer when receiving device data.
It specifically, can timing when receiving device data for the first time.
S33: to the device data received in the prefixed time interval according to trained after prefixed time interval arrival
Obtained machine learning model is calculated, predict corresponding industrial equipment in the preset time period after current time whether
It will appear failure, and timer reset, restart timing.
It should be noted that the prefixed time interval in the present embodiment can be sufficiently small, thus reach real-time perfoming calculating,
The effect of real-time perfoming prediction.
In a kind of example, data display platform includes WEB server and display terminal, and system structure at this time can join
As shown in Figure 6, step S4 may include sub-step as shown in Figure 7 at this time:
S41:WEB server receives the health information that Distributed Storage platform is sent, and health status is believed
Breath is sent to the display terminal logged in the WEB server.
S42: display terminal shows the health information received.
Here display terminal that is to say the client in Fig. 6, can be fixed terminal, such as computer, can also be with
It is mobile terminal, such as mobile phone, equipment management personnel, which logs in WEB server by display terminal, can inquire each industrial equipment
Health status.
In another example, data display platform can also only include display terminal, display terminal can directly with
Distributed Storage platform interacts, and realizes the inquiry of the health status of industrial equipment.
The present embodiment also provides a kind of processing system of industrial equipment data, shown in Figure 8, comprising: sensor 81,
Gateway 82, wireless sensor network server 83, Distributed Storage platform 84 and data display platform 85,
In, sensor 81 is used to acquire the device data of industrial equipment, and device data is sent to corresponding gateway 82, gateway
Equipment 82 is used to for the device data received being sent to wireless sensor network server 83, the wireless sensor network clothes
Business device 83 calculates the device data received according to trained obtained machine learning model, predicts corresponding industrial equipment
Health information, and corresponding health information is sent to Distributed Storage platform 84 and is stored, data
The health information that display platform 85 is used to be stored according to Distributed Storage platform 84 is good for the industrial equipment of prediction
Health situation is shown.
In some embodiments, wireless sensor network server 83 is also used to parse the device data received
And data obtained after parsing are sent to Distributed Storage platform 84 and are stored.
Specifically, the wireless sensor network server 83 in the present embodiment is used to count the number of the device data received
According to stream length, when determining that data flow length to be processed reaches pre-set length threshold, according to trained obtained machine learning
Model calculates the device data, predicts that corresponding industrial equipment whether can in the preset time period after current time
It breaks down；Or wireless sensor network server 83 for start when receiving device data start timer when,
To the device data received in the prefixed time interval according to trained obtained machine learning after prefixed time interval arrival
Model is calculated, and predicts whether corresponding industrial equipment will appear failure in the preset time period after current time, and
Timer is reset, timing is restarted.
Data display platform in the present embodiment may include WEB server and display terminal, specifically be referred to
The introduction in face, which is not described herein again.
The processing method and system of industrial equipment data provided in this embodiment acquire setting for industrial equipment by sensor
Standby data, and the device data is sent to corresponding gateway, the device data received is sent to by each gateway
Wireless sensor network server, wireless sensor network server is according to trained obtained machine learning model to receiving
Device data calculated, predict the health information of corresponding industrial equipment, and corresponding health information is sent
It is stored to Distributed Storage platform, the health status that data display platform is stored according to Distributed Storage platform
Information shows the health status of the industrial equipment of prediction, scheme provided by the invention take full advantage of technology of Internet of things,
Big data technology and machine learning techniques, the device data based on sensor acquisition are predicted that improve data uses valence
Value, keeps the management of factory more intelligent, reduces the investment of human resources.
It is noted that herein, the terms "include", "comprise" or its any other variant are intended to non-exclusive
Property include so that include a series of elements process, method, article or device not only include those elements, but also
Further include other elements that are not explicitly listed, or further include for this process, method, article or device it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that wanted including this
There is also other identical elements in the process, method of element, article or device.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in a storage medium
In (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that a terminal (can be mobile phone, computer, service
Device, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited to above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than restrictive, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form, all of these belong to the protection of the present invention.
Claims (10)
1. a kind of processing method of industrial equipment data characterized by comprising
S1: the device data of each sensor acquisition industrial equipment, and the device data is sent to corresponding gateway；
S2: the device data received is sent to wireless sensor network server by each gateway；
S3: the wireless sensor network server is according to trained obtained machine learning model to the equipment received
Data are calculated, and predict the health information of corresponding industrial equipment, and corresponding health information is sent to distribution
Formula data storing platform is stored；
S4: data display platform sets the industry of prediction according to the health information that the Distributed Storage platform stores
Standby health status is shown.
2. the processing method of industrial equipment data as described in claim 1, which is characterized in that the device data includes equipment
At least one of electricity consumption data, device temperature data and equipment humidity data.
3. the processing method of industrial equipment data as described in claim 1, which is characterized in that after the S2, further includes:
The wireless sensor network server carries out parsing to the device data received and by number obtained after parsing
It is stored according to the Distributed Storage platform is sent to.
4. the processing method of industrial equipment data as described in claim 1, which is characterized in that the S3 includes:
S30: the data flow length for the device data that the wireless sensor network server statistics receives；
S32: when determining that data flow length to be processed reaches pre-set length threshold, according to trained obtained machine learning mould
Type calculates the device data, predicts whether corresponding industrial equipment can go out in the preset time period after current time
Existing failure.
5. the processing method of industrial equipment data as described in claim 1, which is characterized in that the S3 includes:
S31: when the wireless sensor network server starts to start timer when receiving the device data；
S33: the device data received in the prefixed time interval is obtained according to trained after prefixed time interval arrival
Machine learning model calculated, predict whether corresponding industrial equipment can go out in the preset time period after current time
Existing failure, and timer is reset, he restarts timing.
6. the processing method of industrial equipment data as described in claim 1, which is characterized in that the data display platform includes
WEB server and display terminal, the S4 include:
S41: the WEB server receives the health information that the Distributed Storage platform is sent, and will be described strong
Health condition information is sent to the display terminal logged in the WEB server；
S42: the display terminal shows the health information received.
7. the processing method of industrial equipment data as claimed in any one of claims 1 to 6, which is characterized in that the S4 includes:
The health information that the data display platform is stored according to the Distributed Storage platform is by the industry of prediction
The health status of equipment is shown by icon and/or report and/or text.
8. a kind of processing system of industrial equipment data characterized by comprising sensor, gateway, wireless sensor network
Network server, Distributed Storage platform and data display platform；
The sensor is used to acquire the device data of industrial equipment, and the device data is sent to corresponding gateway and is set
It is standby；
The gateway is used to the device data received being sent to wireless sensor network server；
The wireless sensor network server is used for according to trained obtained machine learning model to setting described in receiving
Standby data are calculated, and predict the health information of corresponding industrial equipment, and corresponding health information is sent to institute
Distributed Storage platform is stated to be stored；
The health information that the data display platform is used to be stored according to the Distributed Storage platform is by prediction
The health status of industrial equipment is shown.
9. the processing system of industrial equipment data as claimed in claim 8, which is characterized in that the wireless sensor network clothes
Business device is also used to carry out the device data received to parse and data obtained after parsing are sent to the distribution
Data storing platform is stored.
10. the processing system of industrial equipment data as claimed in claim 8, which is characterized in that the wireless sensor network
Server is used to count the data flow length of the device data received, reaches default length in the data flow length for determining to be processed
When spending threshold value, the device data is calculated according to trained obtained machine learning model, predicts corresponding industrial equipment
Whether will appear failure in preset time period after current time；Or the wireless sensor network server is for connecing
It is inscribed to the prefixed time interval after prefixed time interval arrival when starting to start timer when receiving the device data
The device data received is calculated according to trained obtained machine learning model, predicts corresponding industrial equipment when current
Whether will appear failure in preset time period after quarter, and timer is reset, restarts timing.
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