CN111222653A - Method and system for intelligently making maintenance plan of high-altitude operation equipment by combining internet of things - Google Patents
Method and system for intelligently making maintenance plan of high-altitude operation equipment by combining internet of things Download PDFInfo
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Abstract
The invention discloses an intelligent high-altitude operation equipment maintenance plan making system realized by combining polymer networking and an implementation method thereof.
Description
Technical Field
The invention belongs to the technical field of computer software, relates to the technology of Internet of things and artificial intelligence, and particularly relates to an intelligent system for making a maintenance plan of overhead working equipment by combining Internet of things and an implementation method thereof.
Background
The application of the internet of things technology in various industries tends to be mature, and in the application of high-altitude platform equipment, the internet of things is also used for collecting data, namely equipment information is collected and transmitted to a background system through information sensing equipment such as a sensor and a global positioning system according to an agreed protocol. However, the information collected at present is single, and only includes equipment positioning, working time and the like.
High altitude platform equipment needs to maintain according to the plan, and unified maintenance plan is formulated according to the data of the equipment maintenance standard of standard and thing networking collection to our maintenance plan now, has following problem: because according to the general maintenance standard, only the time interval and the working time length of maintenance are referred to, the equipment is uniformly and periodically maintained without difference, and the damage to accessories caused by different construction environments or the equipment with serious loss cannot be identified and maintained in time.
Disclosure of Invention
In order to solve the problems, the invention discloses an intelligent formulation method of a maintenance plan of overhead working equipment realized by the aid of polymer networking and a system capable of realizing the method.
In order to achieve the purpose, the invention provides the following technical scheme:
the intelligent formulation method of the maintenance plan of the high-altitude operation equipment realized by combining internet of things comprises the following steps:
step 1, establishing a communication link between equipment information carried by a high-altitude platform equipment terminal and a cloud;
step 2, the high-altitude platform equipment terminal uploads terminal state information to the cloud regularly, wherein the state information at least comprises operation duration, battery state, real-time position and charging frequency;
step 3, the cloud receives the terminal state and processes the terminal state, the state data is distributed to an alarm link and a data link through a flash system to be processed, the alarm link processes the state data which can be used for alarm judgment, the alarm link judges whether to trigger alarm or not through a preset threshold and a preset rule, and the data link cleans and normalizes the data;
step 4, the cloud loss calculation platform extracts all indexes in the state information, encodes the indexes into a feature vector set, and then calls an equipment loss degree analysis model to judge the loss coefficient;
the equipment loss degree analysis model is specifically established through the following processes:
1) the critical factors are clearly affected by the degree of loss: real-time running state data of equipment, the field of engineering construction, the type of engineering operation, the service life of the equipment and the last maintenance time interval;
2) quantifying the factors determined in the step 1), and adopting the following indexes as equipment loss degree identification indexes: running time length R, battery state B, charging frequency F, construction field index C, operation type index A and last maintenance time interval I;
3) setting different weights for different factors based on the quantized factors, wherein R is the weight of an operation time length factor R, B is the weight of a battery state B, F is the weight of a charging frequency F, C is the weight of a construction field index C, a is the weight of an operation type index A, and I is the weight of a last maintenance time interval I; the loss factor is calculated by:
loss factor ═ (R × R% + B% + F × F% + C% + a% + I × I%)/(R + B + F + C + a + I);
step 5, when the loss coefficient exceeds a specified threshold value, carrying out classification work order delegation according to the severity level;
and 6, multiplying a loss coefficient by the standard maintenance period of each part of the equipment, and calculating the maintenance time interval according to the following formula:
the maintenance time interval is min (maintenance item 1 cycle loss factor 1, maintenance item 2 cycle loss factor 2, …, maintenance item n cycle loss factor n)
The equipment maintenance schedule time is calculated by the following formula:
the estimated maintenance date is the last maintenance date plus the present maintenance interval.
The invention also provides an intelligent maintenance plan making system of the aerial working equipment realized by the polymer network, which comprises an Internet of things platform and a cloud end, wherein the Internet of things platform acquires data through a sensor arranged on the aerial platform equipment, establishes data connection with the cloud end, and uploads terminal state information to the cloud end at regular time; the loss calculation platform calculates a loss coefficient according to data uploaded by the Internet of things platform and by combining the equipment loss analysis model, and the loss coefficient calculation formula is as follows:
loss coefficient ═ (R × R% + B × B% + F × F% + C × C% + a × a% + I × I%)/(R + B + F + C + a + I)
When the loss coefficient exceeds a threshold value, issuing alarm information and assigning a work order; and multiplying the standard cycle of maintenance of each accessory of the equipment by a loss coefficient by the maintenance plan making platform, and calculating to obtain a maintenance time interval by the following formula:
the maintenance time interval is min (maintenance item 1 cycle loss factor 1, maintenance item 2 cycle loss factor 2, …, maintenance item n cycle loss factor n)
The equipment maintenance schedule time is calculated by the following formula:
the estimated maintenance date is the last maintenance date plus the present maintenance interval.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the intelligent maintenance planning method and system based on the Internet of things receive data fed back by the intelligent terminal of the Internet of things, collect diversified data such as operation time length, battery state, real-time position, engine and charging habit of the equipment in real time, design an equipment loss degree analysis model by combining big data of platform precipitation, and finally calculate reasonable equipment maintenance planning time according to the standard period multiplied by loss coefficients of maintenance of all parts of the equipment, so that intelligent establishment of an equipment maintenance plan of the aerial work platform is realized, the equipment failure rate is reduced, the resource operation efficiency is improved, and a unified maintenance plan standard can be established according to maintenance periods and project suggestions given by different equipment manufacturers.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
The technical solutions provided by the present invention will be described in detail below with reference to specific examples, and it should be understood that the following specific embodiments are only illustrative of the present invention and are not intended to limit the scope of the present invention. Additionally, the steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions and, although a logical order is illustrated in the flow charts, in some cases, the steps illustrated or described may be performed in an order different than here.
The process of the method for intelligently making the maintenance plan of the high-altitude operation equipment realized by the combination internet is shown in figure 1, and comprises the following steps:
step 1, a high-altitude platform equipment terminal carries equipment information to initiate an authentication application to a cloud and construct a websocket long link;
step 2, the high-altitude platform equipment terminal uploads terminal state information to the cloud regularly through the websocket, and the state information comprises the working hours: total working hours of the current equipment, power battery voltage: unit v, range 0-600, longitude: to one part per million, latitude: accurate to one millionth, based on the data, the cloud end can calculate data such as running time, battery state, real-time position, charging frequency and the like.
And 3, after receiving the terminal state, the cloud distributes the state data to two links through a flash system for processing, wherein the two links comprise an alarm link and a data link. The alarm link processes state data which can be used for alarm judgment, and judges whether to trigger an alarm or not through a preset threshold value and a preset rule, if the abnormal change occurs in the 'engine state' data acquired by a certain type of equipment. Then an alarm is sent to the relevant personnel to judge whether the equipment of the type has defects generally or not, whether the equipment needs to be confirmed by a manufacturer or not, and the like. The data link cleans and normalizes the data (unifies the data format and eliminates abnormal data) and injects the data into hdfs (Hadoop distributed file system) of a big data platform.
And 4, the cloud loss calculation platform extracts various indexes in the state information by using the calculation capacity (mapreduce) of the big data platform, encodes the indexes into a feature vector set, and calls an equipment loss analysis model to judge the loss coefficient.
The equipment loss degree analysis model is combined with data of platform sediment, and the portrait and historical maintenance data of the project where the equipment is located are analyzed, so that loss degrees of all accessories of the equipment are finally determined, and the equipment loss degree analysis model is specifically established through the following processes.
1) The critical factors are clearly affected by the degree of loss: real-time running state data of equipment, the field of engineering construction, the type of engineering operation, the service life of the equipment and the last maintenance time interval;
2) factor quantification: the following indexes are adopted as equipment loss degree identification indexes
An operation duration (R) calculated from the data acquired by the sensor, the unit being hours, the operation duration being the number of hours corresponding to the current date-the number of hours corresponding to the last maintenance date.
Battery state (B), which is calculated from data acquired by the sensor, and is 1-max (operating time/threshold 1, factory time/threshold 2).
Charging frequency (F) calculated from data acquired by the sensor, and when "power battery voltage" is greater than threshold 3, the state of charge is counted once. And counting the charging times between the current date and the last maintenance date as the charging frequency.
Construction field index (C): and acquiring all operation engineering histories in the current maintenance period of the equipment. And formulating different scores according to the influence degree of the engineering construction field on the equipment loss degree. For example, in the projects of 'chemical smelting material type plants', the loss influence on equipment is large, and the value is high; the index should be set in conjunction with historical data. The corresponding factor values C under different maintenance items may also be different, and specifically, the determination rule may be set as required.
Job type index (a): and acquiring all operation engineering histories in the current maintenance period of the equipment. And (4) formulating different scores according to the influence degree of the engineering operation type on the equipment loss degree. For example, the operation of fire-proof paint has large influence on the appearance loss of equipment and higher score; the index should be set in conjunction with historical data. The corresponding factor values a under different maintenance items may also be different, and specifically, the determination rule may be set as required.
The maintenance period (D) of the equipment, different maintenance standards (as shown in table 1) are established for different maintenance items of different manufacturers and different equipment models, and data is stored in the platform in advance.
The last maintenance time interval (I), different manufacturers and different equipment models are set up with different maintenance time interval standards, and the data is stored on the platform in advance.
3) Determining a device loss coefficient model: firstly, a model is built through a rule engine, and the implementation mode is as follows: based on the quantized factors, different weights are set for different factors, and finally, a definite value of the loss coefficient is output.
Setting a weight based on each factor, wherein R is the weight of the running time length factor R, B is the weight of the battery state B, F is the weight of the charging frequency F, C is the weight of the construction field index C, a is the weight of the operation type index A, and I is the weight of the last maintenance time interval I.
Loss coefficient ═ (R × R% + B × B% + F × F% + C × C% + a × a% + I × I%)/(R + B + F + C + a + I)
Obviously, since the construction field index C, the operation type index a, and the equipment maintenance period D are different depending on the maintenance items, the wear factor may be different for different maintenance items in the same equipment.
And 5, when the loss coefficient exceeds a specified threshold value, analyzing equipment information (the area, the loss degree and the type of maintenance spare parts) and service engineer information (the area, the skill level and the task saturation degree of the day) to distribute the work order.
And 6, multiplying the standard cycle of maintenance of each part of the equipment by a loss coefficient to calculate reasonable equipment maintenance planning time. The standard maintenance cycle for each component of the equipment is the maintenance cycle and the project recommendation given by different equipment manufacturers, as shown in table 1 below.
TABLE 1
The maintenance time interval is min (maintenance item 1 cycle loss factor 1, maintenance item 2 cycle loss factor 2, …, maintenance item n cycle loss factor n)
Predicted maintenance date is the last maintenance date plus the interval between the previous maintenance and the current maintenance
Therefore, the next estimated maintenance date is obtained, and a more reasonable and closer to the actual maintenance plan is obtained.
The invention also provides an intelligent maintenance plan making system for the aerial working equipment realized by the polymer network, which can realize the method and comprises an Internet of things platform and a cloud, wherein the platform of the Internet of things collects data (including working hours, power battery voltage, longitude, latitude and the like) through a sensor arranged on the high-altitude platform equipment, and establishes data connection with the cloud end, and uploads end state information to the cloud end at regular time, the cloud end comprises a flash system, a loss calculation platform and a maintenance plan making platform, wherein the flash system is used for dividing the terminal state information into two links, namely an alarm link and a data link, the alarm link judges whether to trigger an alarm according to a preset threshold value and a preset rule, and the data link cleans and normalizes the data and then injects the data into hdfs (Hadoop distributed file system) of a large data platform, namely, the content in the step 3 is executed; and (3) calculating a loss coefficient by the loss calculation platform according to data uploaded by the Internet of things platform and by combining the equipment loss analysis model, assigning a work order when the loss coefficient exceeds a threshold value, namely executing the contents of the steps 4 and 5, multiplying the loss coefficient by the maintenance plan making platform according to a standard period of maintenance of each accessory of the equipment to obtain a proper maintenance period, calculating reasonable equipment maintenance plan time, namely executing the content of the step 6.
The technical means disclosed in the invention scheme are not limited to the technical means disclosed in the above embodiments, but also include the technical scheme formed by any combination of the above technical features. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and such improvements and modifications are also considered to be within the scope of the present invention.
Claims (2)
1. The method for intelligently making the maintenance plan of the high-altitude operation equipment by combining internet of things is characterized by comprising the following steps of:
step 1, establishing a communication link between equipment information carried by a high-altitude platform equipment terminal and a cloud;
step 2, the high-altitude platform equipment terminal uploads terminal state information to the cloud regularly, wherein the state information at least comprises operation duration, battery state, real-time position and charging frequency;
step 3, the cloud receives the terminal state and processes the terminal state, the state data is distributed to an alarm link and a data link through a flash system to be processed, the alarm link processes the state data which can be used for alarm judgment, the alarm link judges whether to trigger alarm or not through a preset threshold and a preset rule, and the data link cleans and normalizes the data;
step 4, the cloud loss calculation platform extracts all indexes in the state information, encodes the indexes into a feature vector set, and then calls an equipment loss degree analysis model to judge the loss coefficient;
the equipment loss degree analysis model is specifically established through the following processes:
1) the critical factors are clearly affected by the degree of loss: real-time running state data of equipment, the field of engineering construction, the type of engineering operation, the service life of the equipment and the last maintenance time interval;
2) quantifying the factors determined in the step 1), and adopting the following indexes as equipment loss degree identification indexes: running time length R, battery state B, charging frequency F, construction field index C, operation type index A and last maintenance time interval I;
3) setting different weights for different factors based on the quantized factors, wherein R is the weight of an operation time length factor R, B is the weight of a battery state B, F is the weight of a charging frequency F, C is the weight of a construction field index C, a is the weight of an operation type index A, and I is the weight of a last maintenance time interval I; the loss factor is calculated by:
loss factor ═ (R × R% + B% + F × F% + C% + a% + I × I%)/(R + B + F + C + a + I);
step 5, when the loss coefficient exceeds a specified threshold value, carrying out classification work order delegation according to the severity level;
and 6, multiplying a loss coefficient by the standard maintenance period of each part of the equipment, and calculating the maintenance time interval according to the following formula:
the maintenance time interval is min (maintenance item 1 cycle loss factor 1, maintenance item 2 cycle loss factor 2, …, maintenance item n cycle loss factor n)
The equipment maintenance schedule time is calculated by the following formula:
the estimated maintenance date is the last maintenance date plus the present maintenance interval.
2. Combine high altitude construction equipment maintenance plan intelligence system that thing networking realized, its characterized in that: the system comprises an Internet of things platform and a cloud, wherein the Internet of things platform acquires data through a sensor arranged on high-altitude platform equipment, establishes data connection with the cloud, and uploads terminal state information to the cloud at regular time; the loss calculation platform calculates a loss coefficient according to data uploaded by the Internet of things platform and by combining the equipment loss analysis model, and the loss coefficient calculation formula is as follows:
loss coefficient ═ (R × R% + B × B% + F × F% + C × C% + a × a% + I × I%)/(R + B + F + C + a + I)
When the loss coefficient exceeds a threshold value, issuing alarm information and assigning a work order; and multiplying the standard cycle of maintenance of each accessory of the equipment by a loss coefficient by the maintenance plan making platform, and calculating to obtain a maintenance time interval by the following formula:
the maintenance time interval is min (maintenance item 1 cycle loss factor 1, maintenance item 2 cycle loss factor 2, …, maintenance item n cycle loss factor n)
The equipment maintenance schedule time is calculated by the following formula:
the estimated maintenance date is the last maintenance date plus the present maintenance interval.
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Cited By (5)
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| CN112183778A (en) * | 2020-09-18 | 2021-01-05 | 安徽三禾一信息科技有限公司 | Management system for equipment maintenance service |
| CN113282467A (en) * | 2021-05-28 | 2021-08-20 | 青岛海尔科技有限公司 | Information display method and device, storage medium and electronic device |
| CN113298380A (en) * | 2021-05-25 | 2021-08-24 | 东莞嘉誉诚建设基础工程有限公司 | Method, system, equipment and storage medium for managing pile machine equipment |
| CN114035466A (en) * | 2021-11-05 | 2022-02-11 | 肇庆高峰机械科技有限公司 | Control system of duplex position magnetic sheet arrangement machine |
| CN115545234A (en) * | 2022-10-14 | 2022-12-30 | 北京远舢智能科技有限公司 | Equipment maintenance system based on accumulated time length |
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