CN111397930A - Construction equipment fault detection and risk intelligent early warning system and method - Google Patents
Construction equipment fault detection and risk intelligent early warning system and method Download PDFInfo
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- CN111397930A CN111397930A CN202010187128.9A CN202010187128A CN111397930A CN 111397930 A CN111397930 A CN 111397930A CN 202010187128 A CN202010187128 A CN 202010187128A CN 111397930 A CN111397930 A CN 111397930A
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Abstract
The invention discloses a construction equipment fault detection and risk intelligent early warning system and a method, wherein the system comprises a data acquisition module, a diagnosis module, a storage module and a server terminal; the data acquisition module is used for acquiring the state data of the construction equipment and transmitting the state data to the server terminal; the server terminal is used for setting fault parameters and early warning parameters of the construction equipment; the diagnostic module is also used for sending the received state data to the storage module and the diagnostic module; the diagnosis module is used for receiving the state data transmitted by the server terminal, performing health diagnosis on the state data and feeding back a diagnosis result to the server terminal; and the storage module is used for receiving and storing the data transmitted to the storage module. The invention aims to provide a construction equipment fault detection and risk intelligent early warning system and method, which solve the problems of alarm rigor, insufficient types, serious limitation of personal experience, early warning instantaneity, insufficient forecast and the like of construction field engineering equipment.
Description
Technical Field
The invention relates to the technical field of engineering construction, in particular to a construction equipment fault detection and risk intelligent early warning system and method.
Background
Whether the construction equipment can work normally is directly related to the achievement of construction progress and a target, but is limited by less software and hardware configuration of the equipment, insufficient experience and lack of responsibility of equipment users, and difficult judgment on whether the equipment has faults, needs to be maintained and the like.
Currently, there are three methods used by equipment users to determine the failure and risk of construction equipment:
firstly, the device fault indicator lamp or related instrument is carried by the device when the device leaves the factory. The disadvantages of this method are: the types of faults and alarms carried by the equipment are few, and the fault mode cannot be adjusted after the equipment is out of the field, so that the fault early warning requirements of the equipment at different life cycle stages cannot be met.
And secondly, comprehensive judgment is carried out by synthesizing multidimensional information such as noise, vibration, temperature and the like through the use experience of an individual. The disadvantages of this method are: the method is seriously dependent on the experience level of users, and the users who are not used for a long time are difficult to correctly judge, and the possibility of misjudgment is high.
And thirdly, judging through professional regular maintenance. The disadvantages of this method are: firstly, due to the limitation of field management level and responsibility of users, regular professional maintenance can not be implemented, and the situation that equipment is used without maintenance and then repaired after serious faults occur frequently; secondly, maintaining normal equipment, consuming maintenance cost, reducing equipment utilization rate and delaying construction progress; finally, the timeliness of regular maintenance is not enough, and the situation that maintenance equipment fails frequently occurs on site.
Disclosure of Invention
The invention aims to provide a construction equipment fault detection and risk intelligent early warning system and method, which solve the problems of alarm rigor, insufficient types, serious limitation of personal experience, early warning instantaneity, insufficient forecast and the like of construction field engineering equipment.
The invention is realized by the following technical scheme:
a construction equipment fault detection and risk intelligent early warning system comprises a data acquisition module, a diagnosis module, a storage module and a server terminal;
the data acquisition module is arranged on the construction equipment and used for acquiring the state data of the construction equipment and transmitting the acquired state data to the server terminal;
the server terminal is used for setting the fault parameters and the early warning parameters of the construction equipment and transmitting the set fault parameters and the set early warning parameters to the storage module for storage; the data acquisition module is used for acquiring state data transmitted by the data acquisition module and transmitting the received state data to the storage module and the diagnosis module;
the diagnosis module is used for receiving the state data transmitted by the server terminal, carrying out health diagnosis on the construction equipment according to the acquired state data and the fault parameters set by the server terminal, and simultaneously feeding back a diagnosis result to the server terminal;
the storage module is used for receiving and storing the data transmitted to the storage module.
When the system is used, firstly, the workers of the construction equipment classify the faults which are easy to appear on the construction equipment at the server terminal, fault parameters and early warning parameters which are related to various faults are set according to the classification condition of the faults, then the data acquisition module transmits state data (such as temperature, noise, vibration and the like) of the construction equipment to the diagnosis module at regular time, and the diagnosis module compares the state data transmitted by the data acquisition module with the fault parameters or the early warning parameters which are set by the server terminal so as to judge the health state of the construction equipment. If the construction equipment has a problem or is about to have a problem, fault information or early warning is fed back to the server, and workers can conveniently and timely handle the fault information or early warning. Meanwhile, due to the fact that the faults of the construction equipment are classified in advance, when early warning occurs to the construction equipment, workers do not need to judge the faults of the construction equipment according to self experiences, and limitation on professional degree of the workers is greatly reduced.
Further, the fault parameters set by the server terminal include a plurality of fault modes, a plurality of fault parameters and a plurality of fault parameter thresholds; wherein any of the failure modes includes one or more of the failure parameters and the failure parameter threshold corresponding to each of the failure parameters. When the construction equipment breaks down, the fault information can be fed back to the server terminal in a more detailed manner, and the maintenance of the construction equipment can be completed quickly by the staff conveniently.
The early warning parameters set by the server terminal further comprise a plurality of early warning modes and a plurality of early warning parameters; wherein any of the early warning modes includes one or more of the early warning parameters.
Further, the diagnosis module comprises a fault diagnosis unit, a storage unit, a learning unit and a risk early warning unit;
the fault diagnosis unit is configured to receive the state data transmitted by the server terminal, compare the received state data with the fault parameter threshold stored in the storage module, and if the received state data is greater than the fault parameter threshold, feed back the fault mode information corresponding to the fault parameter threshold to the server terminal for fault alarm, and store the fault mode information in the storage module; if the received state data is smaller than the fault parameter threshold value, transmitting the state data to the risk early warning unit;
the learning unit is used for intelligently learning the fault mode information and the state data stored in the storage module to obtain the early warning parameter threshold corresponding to the early warning parameter, and storing the early warning parameter threshold to the storage unit;
the risk early warning unit is used for receiving the state data transmitted by the fault diagnosis unit, comparing the received state data with the early warning parameter threshold value stored in the storage unit, and feeding back the received state data to the server terminal for risk early warning if the received state data is greater than the early warning parameter threshold value; otherwise, no processing is performed.
The data acquisition module transmits the state data once, and the diagnosis module diagnoses the state data, so that the accuracy of fault diagnosis of the construction equipment can be improved, and the maintenance efficiency of the construction equipment by workers can be improved; the equipment can be maintained according to the early warning information, and the service life of the construction equipment is effectively prolonged.
The wireless transmission module is connected with the data acquisition module and the server terminal and is used for transmitting the state data acquired by the data acquisition module to the server terminal. The wireless transmission does not need wiring, is not limited by geographic environment and working content, and has low construction difficulty, strong capacity expansion capability and convenient maintenance.
Further, the server terminal is set as a mobile phone. The mobile phone is mature in technology, easy to carry and widely applied to people, and when the system breaks down or carries out risk early warning, workers can quickly process the system.
A construction equipment fault detection and risk intelligent early warning method comprises the following steps:
setting fault parameters and early warning parameters of the construction equipment;
acquiring state data of the construction equipment;
and carrying out health diagnosis on the construction equipment according to the set fault parameters and the acquired state data, and judging whether the construction equipment has faults or risks.
The method can judge the health state of the construction equipment. When the construction equipment has problems or is about to have problems, the construction equipment can be fed back to the working personnel, and the working personnel can conveniently and timely process the construction equipment. Meanwhile, due to the fact that the faults of the construction equipment are classified in advance, when early warning occurs to the construction equipment, workers do not need to judge the faults of the construction equipment according to self experiences, and limitation on professional degree of the workers is greatly reduced.
Further, the setting of the fault parameter specifically includes:
setting a plurality of different failure modes;
setting fault parameters matched with any fault mode;
setting a fault parameter threshold corresponding to any of the fault parameters.
Further, the setting of the early warning parameters specifically includes:
setting a plurality of different early warning modes;
setting early warning parameters matched with any early warning mode;
and learning the fault information and the historical state data of the construction equipment to obtain an early warning parameter threshold corresponding to the early warning parameter.
Further, the health diagnosis specifically includes:
the fault diagnosis is carried out, the acquired state data is compared with the fault parameter threshold, if the state data is larger than the fault parameter threshold, fault alarm is carried out, and otherwise, risk diagnosis is carried out;
and risk diagnosis, namely comparing the state data with the early warning parameter threshold, if the state data is greater than the early warning parameter threshold, carrying out risk early warning, and otherwise, not processing.
The state data is subjected to health diagnosis every time the state data is acquired, so that the accuracy of fault diagnosis of the construction equipment can be improved, and the maintenance efficiency of the construction equipment by workers is improved; the equipment can be maintained according to the early warning information, and the service life of the construction equipment is effectively prolonged.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. and intelligent risk early warning service is provided. The risk early warning is realized by machine learning, learning is automatically carried out from the historical state data and the fault data of the equipment, and the learning result is finally applied to the risk early warning;
2. and the real-time online automatic fault alarm service is provided. The whole process is carried out automatically except for the parameter setting and the checking and learning result part, and the automation degree is high;
3. the diagnosis accuracy of the construction equipment fault is improved through comprehensive judgment of various equipment state data.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Examples
As shown in figure 1 of the drawings, in which,
a construction equipment fault detection and risk intelligent early warning system comprises a data acquisition module, a wireless transmission module, a diagnosis module, a storage module and a server terminal;
the data acquisition module is installed on the construction equipment, is connected with the wireless transmission module and is used for acquiring the state data of the construction equipment and transmitting the acquired state data to the server terminal through the wireless transmission module. In this scheme, wireless transmission module sets up to the bluetooth, and bluetooth has the function of frequency hopping, effectively avoids the ISM frequency band to meet the interference source, therefore bluetooth's security and interference killing feature, and bluetooth's compatibility is better, and is applicable in multiple equipment.
The server terminal is used for setting fault parameters and early warning parameters of the construction equipment; the data acquisition module is used for acquiring state data transmitted by the data acquisition module and transmitting the received state data to the storage module and the diagnosis module.
When a worker sets fault parameters of construction equipment by using a server terminal, firstly, faults which are easy to occur to the construction equipment are classified to obtain a plurality of fault modes, such as visual faults, hidden faults, progressive faults, sudden faults, local faults, overall faults, functional faults, parametric faults and the like, and then fault parameters related to various faults and fault parameter thresholds corresponding to the fault parameters are set according to the classification condition of the faults, such as a pressure threshold of a safety valve system, a valve rod gap threshold of a multi-way valve, an oil mass threshold, a carbon deposition threshold in an engine air compressor, a minimum electric quantity threshold of a generator storage battery and a liquid level threshold of engine coolant. And transmitting the set fault parameters to a storage module for storage.
When the staff sets the early warning parameters of the construction equipment by using the server terminal, the early warning parameters corresponding to each fault mode can be set according to the classified fault modes; and other early warning parameters can be set according to requirements, and the early warning parameters are transmitted to the storage module to be stored.
The more detailed the setting of the fault parameters and the early warning parameters is, the better the fault parameters and the early warning parameters are, when the construction equipment breaks down or early warning occurs, fault information can be fed back to the server terminal in a more detailed mode, and the maintenance of the construction equipment can be completed quickly by workers conveniently.
In this embodiment, the server terminal is set as a mobile phone, the mobile phone is mature in technology, easy to carry and widely applicable to people, and when the system breaks down or the system performs risk early warning, the staff can quickly process the system.
And the storage module is used for receiving and storing the data transmitted to the storage module.
The diagnosis module is used for receiving the state data transmitted by the server terminal, carrying out health diagnosis on the construction equipment according to the acquired state data and the fault parameters set by the server, and simultaneously feeding back the diagnosis result to the server terminal;
in this embodiment, the diagnosis module includes a fault diagnosis unit, a storage unit, a learning unit, and a risk early warning unit;
the fault diagnosis unit is used for receiving the state data transmitted by the server terminal, comparing the received state data with a fault parameter threshold value stored in the storage module, and if the received state data is greater than the fault parameter threshold value, feeding back fault mode information corresponding to the fault parameter threshold value to the server terminal for fault alarm and storing the fault mode information to the storage module; if the received state data is smaller than the fault parameter threshold value, transmitting the state data to a risk early warning unit;
the learning unit is used for intelligently learning the fault mode information and the state data stored in the storage module to obtain an early warning parameter threshold corresponding to the early warning parameter and storing the early warning parameter threshold to the storage unit;
in the scheme, the learning unit is set to automatically start periodically, and the period is all data between two adjacent fault information. After the learning unit is started, intelligent learning is carried out according to the fault information stored by the storage module and the historical state data of the equipment before the fault occurs, the general rule of the equipment fault is solidified through a big data method, and configuration parameters of risk early warning are formed, so that early warning parameters are more accurate.
The risk early warning unit is used for receiving the state data transmitted by the fault diagnosis unit, comparing the received state data with an early warning parameter threshold value stored in the storage unit, and feeding back the received state data to the server terminal for risk early warning if the received state data is greater than the early warning parameter threshold value; otherwise, no processing is performed.
The data acquisition module transmits the state data once, and the diagnosis module diagnoses the state data, so that the accuracy of fault diagnosis of the construction equipment can be improved, and the maintenance efficiency of the construction equipment by workers can be improved; the equipment can be maintained according to the early warning information, and the service life of the construction equipment is effectively prolonged.
By using the system, the health state of the construction equipment can be judged. When the construction equipment has problems or is about to have problems, the system feeds back fault information or early warning to the server, and workers can conveniently and timely process the fault information or the early warning. Meanwhile, due to the fact that the faults of the construction equipment are classified in advance, when early warning occurs to the construction equipment, workers do not need to judge the faults of the construction equipment according to self experiences, and limitation on professional degree of the workers is greatly reduced.
A construction equipment fault detection and risk intelligent early warning method comprises the following steps:
setting fault parameters and early warning parameters of construction equipment;
acquiring state data of construction equipment;
and carrying out health diagnosis on the construction equipment according to the set fault parameters and the acquired state data, and judging whether the construction equipment has faults or risks.
In this embodiment, the fault parameters and the early warning parameters of the construction equipment are set by a worker, when the worker sets the fault parameters of the construction equipment, the faults which easily occur to the construction equipment are firstly classified to obtain a plurality of fault modes, such as visual faults, hidden faults, progressive faults, sudden faults, local faults, overall faults, functional faults, parametric faults and the like, and then fault parameters related to various faults and fault parameter thresholds corresponding to the fault parameters are set according to the classification condition of the faults, such as a safety valve system pressure threshold, a multi-way valve rod gap threshold, an oil quantity threshold, a carbon deposition threshold in an engine air compressor, a generator storage battery minimum electric quantity threshold and an engine coolant liquid level threshold.
When the early warning parameters of the construction equipment are set by the staff, early warning parameter thresholds corresponding to the fault modes can be set according to the classified fault modes; and other early warning parameter thresholds can be set according to requirements. Wherein the early warning parameter threshold is obtained by big data analysis. In the scheme, intelligent learning is regularly carried out on all data between the last two faults of the construction equipment, and the general rule of the faults of the construction equipment is solidified through big data analysis to obtain the early warning parameter threshold value.
When the fault parameters and the early warning parameters are set, the state data of the construction equipment can be acquired on line, and in order to reduce the data processing amount, the state data of the construction equipment can be set to be collected in one group every hour.
Comparing the acquired state data with a fault parameter threshold, and if the state data is greater than the fault parameter threshold, performing fault alarm; and if not, comparing the state data with the early warning parameter threshold, if the state data is greater than the early warning parameter threshold, performing risk early warning, otherwise, not processing.
The method can judge the health state of the construction equipment. When the construction equipment has problems or is about to have problems, the construction equipment can be fed back to the working personnel, and the working personnel can conveniently and timely process the construction equipment. Meanwhile, due to the fact that the faults of the construction equipment are classified in advance, when early warning occurs to the construction equipment, workers do not need to judge the faults of the construction equipment according to self experiences, and limitation on professional degree of the workers is greatly reduced.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A construction equipment fault detection and risk intelligent early warning system is characterized by comprising a data acquisition module, a diagnosis module, a storage module and a server terminal;
the data acquisition module is arranged on the construction equipment and used for acquiring the state data of the construction equipment and transmitting the acquired state data to the server terminal;
the server terminal is used for setting the fault parameters and the early warning parameters of the construction equipment and transmitting the set fault parameters and the set early warning parameters to the storage module for storage; the data acquisition module is used for acquiring state data transmitted by the data acquisition module and transmitting the received state data to the storage module and the diagnosis module;
the diagnosis module is used for receiving the state data transmitted by the server terminal, carrying out health diagnosis on the construction equipment according to the acquired state data and the fault parameters set by the server terminal, and simultaneously feeding back a diagnosis result to the server terminal;
the storage module is used for receiving and storing the data transmitted to the storage module.
2. The intelligent construction equipment fault detection and risk early warning system according to claim 1, wherein the fault parameters set by the server terminal comprise a plurality of fault modes, a plurality of fault parameters and a plurality of fault parameter thresholds; wherein any of the failure modes includes one or more of the failure parameters and the failure parameter threshold corresponding to each of the failure parameters.
3. The intelligent construction equipment fault detection and risk early warning system according to claim 2, wherein the early warning parameters set by the server terminal comprise a plurality of early warning modes and a plurality of early warning parameters; wherein any of the early warning modes includes one or more of the early warning parameters.
4. The construction equipment fault detection and risk intelligent early warning system according to claim 3, wherein the diagnosis module comprises a fault diagnosis unit, a storage unit, a learning unit and a risk early warning unit;
the fault diagnosis unit is configured to receive the state data transmitted by the server terminal, compare the received state data with the fault parameter threshold stored in the storage module, and if the received state data is greater than the fault parameter threshold, feed back the fault mode information corresponding to the fault parameter threshold to the server terminal for fault alarm, and store the fault mode information in the storage module; if the received state data is smaller than the fault parameter threshold value, transmitting the state data to the risk early warning unit;
the learning unit is used for intelligently learning the fault mode information and the state data stored in the storage module to obtain the early warning parameter threshold corresponding to the early warning parameter, and storing the early warning parameter threshold to the storage unit;
the risk early warning unit is used for receiving the state data transmitted by the fault diagnosis unit, comparing the received state data with the early warning parameter threshold value stored in the storage unit, and feeding back the received state data to the server terminal for risk early warning if the received state data is greater than the early warning parameter threshold value; otherwise, no processing is performed.
5. The construction equipment fault detection and risk intelligent early warning system according to any one of claims 1-4, further comprising a wireless transmission module, wherein the wireless transmission module is connected with the data acquisition module and the server terminal, and is used for transmitting the state data acquired by the data acquisition module to the server terminal.
6. The construction equipment fault detection and risk intelligent early warning system as claimed in claim 5, wherein the server terminal is set as a mobile phone.
7. A construction equipment fault detection and risk intelligent early warning method is characterized by comprising the following steps:
setting fault parameters and early warning parameters of the construction equipment;
acquiring state data of the construction equipment;
and carrying out health diagnosis on the construction equipment according to the set fault parameters and the acquired state data, and judging whether the construction equipment has faults or risks.
8. The construction equipment fault detection and risk intelligent early warning method according to claim 7, wherein the fault parameter setting specifically comprises:
setting a plurality of different failure modes;
setting fault parameters matched with any fault mode;
setting a fault parameter threshold corresponding to any of the fault parameters.
9. The construction equipment fault detection and risk intelligent early warning method according to claim 7 or 8, wherein the early warning parameter setting specifically comprises:
setting a plurality of different early warning modes;
setting early warning parameters matched with any early warning mode;
and learning the fault information and the historical state data of the construction equipment to obtain an early warning parameter threshold corresponding to the early warning parameter.
10. The construction equipment fault detection and risk intelligent early warning method according to claim 9, wherein the health diagnosis specifically comprises:
the fault diagnosis is carried out, the acquired state data is compared with the fault parameter threshold, if the state data is larger than the fault parameter threshold, fault alarm is carried out, and otherwise, risk diagnosis is carried out;
and risk diagnosis, namely comparing the state data with the early warning parameter threshold, if the state data is greater than the early warning parameter threshold, carrying out risk early warning, and otherwise, not processing.
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Application publication date: 20200710 |