Self-diagnosis power outage and transmission method and system for strip mine, medium and product
Through self-diagnosing power outage method and combining environmental and mechanical equipment parameters, intelligent fault detection and power outage decisions are realized, the problem of insufficient manual monitoring in the existing technology is solved, and the accuracy of fault handling and production safety of open-pit mines is improved.
Patent Information
- Application Number
- CN202411200214.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-29
- Publication Date
- 2024-12-06
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In the prior art, fault detection of mechanical equipment and power systems in open-pit mines relies on manual monitoring, which makes it difficult to guarantee real-time and accuracy, and is prone to missed or false alarms, resulting in equipment failures not being discovered and processed in a timely manner, affecting production. Safety and efficiency.
Using the self-diagnostic power outage method, the environmental risk value is calculated and input into the fault diagnosis model by presetting environmental parameter thresholds and mechanical equipment operation parameters, the faulty equipment is determined, and the power outage priority is determined based on the number of faulty equipment, so as to achieve intelligence and refined and provide safe evacuation paths before power outage.
It improves the targetedness and accuracy of power outages, reduces unnecessary production losses and safety hazards, ensures timely handling and workers' safety under high environmental risks, and improves the production efficiency and safety of open-pit mines.
Smart Images
Figure CN119090221A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of power outage in open-pit mines, and in particular to a self-diagnosis power outage method, system, medium and product for open-pit mines. Background Art
[0002] With the development of mining, the scale and complexity of open-pit mines are increasing. In the daily operation of open-pit mines, the safety and stability of various mechanical equipment and power systems are crucial. In order to ensure production safety and efficiency, it is necessary to accurately control the power supply in the mining area, detect and handle equipment failures in a timely manner, and avoid production stagnation or safety accidents caused by equipment failures.
[0003] In the prior art, open-pit mines’ mechanical equipment and power systems are usually maintained through regular inspections and manual monitoring. These methods mainly rely on experienced technicians to evaluate the equipment’s operating status and take necessary power outage measures when abnormal conditions are found. For example, some open-pit mines will set up special monitoring centers to monitor the operating parameters of various equipment in real time, and arrange maintenance and power outage operations based on preset inspection cycles or sudden fault reports. This method can ensure the safe operation of the mine to a certain extent.
[0004] However, as the scale of mining areas expands and the number of equipment increases, the method of relying solely on manual monitoring and regular inspections has gradually exposed its limitations. Specifically, the real-time and accuracy of manual monitoring is difficult to guarantee, and it is easy to miss or report a false alarm, resulting in equipment failures not being discovered and handled in a timely manner. Summary of the invention
[0005] The present application provides a self-diagnosis power outage method, system, medium and product for open-pit mines, which are used to orderly implement power outages through self-diagnosis of equipment failures, thereby improving the safety of the power outage method.
[0006] In the first aspect, the present application provides a self-diagnosis power outage method for open-pit mines, which is applied to the power outage system, and the method includes: determining the environmental risk value of each preset area according to a preset environmental parameter threshold and the environmental parameters of each preset area in the open-pit mine area; when the environmental risk value exceeds the preset environmental risk threshold, inputting the operating parameters of the mechanical equipment in each preset area into a preset fault diagnosis model to determine whether each mechanical equipment has a fault problem; after marking the mechanical equipment with the fault problem as a faulty equipment, obtaining the number of faulty equipment in each preset area; determining the power outage priority of each preset area according to the number of faulty equipment, and sending the power outage priority to the preset power supply control device, so that the power supply device performs power outages on the preset areas in turn, and the more faulty equipment there is, the higher the power outage priority; when it is determined that all faulty equipment in the target preset area has been successfully repaired, controlling the power supply device to supply power to the target preset area.
[0007] In the above embodiment, the power outage system calculates the environmental risk value of each preset area through the environmental parameters of each preset area. When the environmental risk value exceeds the preset environmental risk threshold, it indicates that the environmental conditions of the preset area may pose a threat to the normal operation of the mechanical equipment, or have caused the mechanical equipment to fail. At this time, the power outage system will input the operating parameters of the mechanical equipment in the preset area into the preset fault diagnosis model to determine which mechanical equipment has a fault problem. The power outage system marks the mechanical equipment with a fault problem as a faulty device, and counts the number of faulty devices in each preset area. In this way, the power outage priority of each preset area is determined. The more faulty devices there are in the area, the higher the power outage priority. In order to give priority to the preset areas with more faulty devices and higher risks, so as to reduce potential losses and risks, realize targeted power outage control, and avoid losses caused by comprehensive power outages. This solution makes full use of environmental monitoring and mechanical equipment status data to realize intelligent and refined power outage decisions. Compared with traditional regular or empirical manual power outages, it can detect equipment failures in a timely manner and carry out orderly power outages, improve the pertinence of power outages and the accuracy of decision-making, reduce unnecessary production stoppage losses, and improve the safety and production efficiency of open-pit mines. When all faulty equipment in the target preset area has been repaired and confirmed to be successfully repaired, the power outage system will control the power supply equipment to restore power to the preset area. In this way, the entire process ensures that timely measures can be taken to prevent the expansion of faults in high environmental risk situations, while ensuring the smooth progress of maintenance work and the safety of workers.
[0008] In combination with some embodiments of the first aspect, in some embodiments, according to the preset environmental parameter threshold and the environmental parameters of each preset area of the open-pit mine, the environmental risk value of each preset area is determined, specifically including: The calculation formula of environmental risk value is: R env =ω T *R T +ω P *R P +ω D *R D , where R env represents the environmental risk value, T represents the temperature parameter of each preset area in the open-pit mine, [T min , T max ] represents the preset temperature parameter threshold, P represents the air pressure parameter of each preset area in the open-pit mine, [P min , P max ] represents the preset air pressure parameter threshold, D represents the dust concentration parameter of each preset area in the open-pit mine, [D min , D max ] represents the preset dust concentration threshold, ωT Represents the weight coefficient of the temperature parameter, ω P Represents the weight coefficient of the air pressure parameter, ω D Represents the weight coefficient of the dust concentration parameter and satisfies ω T +ω P +ω D =1.
[0009] In the above embodiment, environmental parameters such as temperature, air pressure and dust concentration will have an impact on mechanical equipment, and the environmental risk value is comprehensively reflected through different weight coefficients, and the evaluation result is more accurate and comprehensive. Compared with the simple judgment threshold, this calculation method can refine the judgment of environmental risks, provide a more reliable basis for subsequent power outage decisions, and improve the accuracy of decisions.
[0010] In combination with some embodiments of the first aspect, in some embodiments, the power outage priority of each preset area is determined according to the number of faulty equipment, and the power outage priority is sent to a preset power supply control device, so that the power supply device performs power outages on the preset areas in turn. The more faulty equipment there is, the higher the power outage priority. Specifically, the following steps are performed: all preset areas are sorted from high to low according to the number of faulty equipment to obtain a power outage priority, wherein the power outage priority includes a first power outage preset area with the highest priority; the power outage priority is sent to the power supply control device, and when the power supply control device performs a power outage on the first power outage preset area at the first power outage moment, a power outage reminder is issued to the first power outage preset area within a preset time period before the first power outage moment.
[0011] In the above embodiment, the power outage system determines the power outage priority by sorting the number of faulty devices in the preset area, thereby achieving an orderly power outage. The preset area with more faulty devices is given priority for power outage, which minimizes the losses caused by the expansion of equipment failures and is highly targeted. The power outage system sends a power outage reminder to the preset area before the power outage, so that the staff can be prepared and the safety of the power outage is improved. Compared with blind and comprehensive power outages, this solution makes the entire power outage process scientific, reasonable and orderly, reduces safety hazards, and improves management efficiency.
[0012] In combination with some embodiments of the first aspect, in some embodiments, when the environmental risk value exceeds a preset environmental risk threshold, the operating parameters of the mechanical equipment in each preset area are input into a preset fault diagnosis model, and before the step of determining whether each mechanical equipment has a fault problem, the method also includes: obtaining operating parameter data of different mechanical equipment under normal operation and fault conditions; using the operating parameter data as input features, and the normal operation and fault conditions of the mechanical equipment as output features; using the input features and the output features to train the preset model to obtain the accuracy of the preset model; when the accuracy exceeds the preset accuracy threshold, obtaining a fault diagnosis model.
[0013] In the above embodiment, by obtaining the operating parameter data of the mechanical equipment and training the model, the automation of fault diagnosis can be achieved. Compared with manual experience judgment, the machine learning model can be trained on the basis of a large amount of data to obtain more accurate fault diagnosis rules. When the accuracy of the preset model exceeds the preset accuracy threshold, the state of the mechanical equipment can be automatically judged, which releases manpower and avoids the possibility of human misjudgment. The entire fault diagnosis process is made intelligent, providing a reliable basis for subsequent power outage decisions.
[0014] In combination with some embodiments of the first aspect, in some embodiments, after sending the power outage priority to the power supply control device, when the power supply control device performs a power outage on the first power outage preset area at the first power outage moment, after the step of issuing a power outage reminder to the first power outage preset area within a preset time period before the first power outage moment, the method also includes: calculating a safe evacuation sorting route for the first power outage preset area based on the entrance and exit location information of the first power outage preset area, the channel information within the area, and the distribution information of the staff in the area, the safe evacuation sorting route being the shortest safe path from each staff position to the nearest entrance and exit; sending the safe evacuation sorting route to a communication terminal within the first power outage preset area, so that the staff evacuates according to the safe evacuation sorting route.
[0015] In the above embodiment, the power outage system sends a power outage reminder to the preset area before the power outage, so that the staff can be prepared, and calculates the safe evacuation route to ensure safe evacuation during the power outage. Compared with the personal safety risks brought by blind power outages, notifying the staff in advance and providing accurate evacuation routes can enable orderly regional evacuation, minimize the risk of safety accidents during power outages, and improve the safety of power outages and maintenance.
[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of determining the environmental risk value of each preset area based on the preset environmental parameter threshold and the environmental parameters of each preset area in the open-pit mine area, the method also includes: when the environmental risk value is lower than the preset environmental risk threshold, generating a safety report corresponding to each preset area based on the environmental risk value and the operating parameters of the mechanical equipment in each preset area.
[0017] In the above embodiment, when the environmental risk value is lower than the preset environmental risk threshold, a safety report corresponding to each preset area is generated, realizing visual monitoring of the status of mechanical equipment. The safety report intuitively displays the status of mechanical equipment and environmental risks, allowing managers to fully understand the current safety status of the mining area and provide a reference for power outage decisions. Compared with simple data, visual reports make information more intuitive, and managers can quickly grasp the overall situation of mechanical equipment operation.
[0018] In combination with some embodiments of the first aspect, in some embodiments, after determining that all faulty equipment in the target preset area has been successfully repaired, and controlling the power supply equipment to supply power to the target preset area, the method also includes: judging whether the operation of each mechanical equipment is stable based on the start-up time and real-time operating parameters of each mechanical equipment in the target preset area; when the operation of the problematic mechanical equipment is unstable, the real-time operating parameters of the problematic mechanical equipment are added to the fault diagnosis model to determine whether to stop the operation of the problematic mechanical equipment.
[0019] In the above embodiment, the power outage system detects the operating status of the mechanical equipment in the preset area where power is restored, and realizes refined control of the start-up of the mechanical equipment. Compared with a simple full restart, this solution can identify mechanical equipment that still has the risk of failure and perform refined processing, thereby avoiding the loss caused by the spread of mechanical equipment failure. This makes the entire power outage and restart process more accurate and controllable, reduces the possibility of repeated power outages, and is conducive to increasing the continuous production time of the mining area.
[0020] In a second aspect, an embodiment of the present application provides a power outage system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the power outage system to execute the method described in the first aspect and any possible implementation method of the first aspect.
[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when executed on a power outage system, enables the power outage system to execute the method described in the first aspect and any possible implementation of the first aspect.
[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a power outage system, causes the power outage system to execute the method described in the first aspect and any possible implementation of the first aspect.
[0023] It can be understood that the power outage system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.
[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Due to the adoption of self-diagnosis technology that comprehensively considers environmental risk values and equipment fault status, intelligent power outage control with strong pertinence and accurate decision-making is achieved, which effectively solves the problems of missed detection, leakage, and false shutdown caused by relying on manual experience judgment in the prior art, thereby significantly improving the safety and production efficiency of power outages. The present invention makes full use of environmental monitoring and operating parameter data of mechanical equipment, and realizes automated fault identification and risk assessment through machine learning and other methods. Compared with traditional manual judgment, the power outage decision of this solution is more accurate and intelligent, avoiding excessive shutdowns and safety hazards, and significantly improving large-scale open-pit mines with complex parameters.
[0025] 2. By adopting the technology of determining priorities by region and orderly power outage, the protection of key areas and important equipment is achieved, and the losses caused by comprehensive power outages in the prior art are effectively solved, thereby maximizing the safety and continuous production capacity of the mining area. The present invention scientifically and rationally determines the power outage priority by ranking the number of faulty equipment in the area, protects key areas and equipment, and significantly reduces unnecessary production stoppage losses compared to traditional blind comprehensive power outages.
[0026] 3. Due to the use of technologies such as calculating the optimal evacuation path and monitoring the restart process, the safety of power outages and maintenance is comprehensively improved, and the evacuation and restart risks existing in the prior art are effectively solved, thereby significantly reducing the possibility of casualties and secondary accidents. The present invention fully considers various safety risks in personnel evacuation and equipment restart, and through technical means such as path planning and real-time monitoring, the entire power outage and maintenance process is more standardized and controllable, greatly improving the safety management level of open-pit mines. BRIEF DESCRIPTION OF THE DRAWINGS
[0027] Figure 1 It is a flow chart of a self-diagnosis power outage method for an open-pit mine in an embodiment of the present application; Figure 2 is another flow chart of the self-diagnosis power outage method for open-pit mines in an embodiment of the present application; Figure 3 It is a schematic diagram of the structure of a physical device of the power outage system in an embodiment of the present application. DETAILED DESCRIPTION
[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.
[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.
[0030] The following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of a self-diagnosis power outage method for an open-pit mine in an embodiment of the present application.
[0031] S101, determining an environmental risk value of each preset area according to a preset environmental parameter threshold and environmental parameters of each preset area of the open-pit mine; The power outage system will continuously monitor the temperature, air pressure, dust concentration and other environmental parameters of each preset area, and refer to the preset temperature threshold, preset air pressure threshold, and preset dust concentration threshold to determine the environmental conditions. For example, the temperature parameter can set the threshold range [30°C, 38°C]. When the temperature in a preset area exceeds 38°C, it will be determined that an environmental risk exists. The power outage system can calculate the comprehensive risk value of multiple environmental parameters, that is, the environmental risk value, and can also determine the risk of a key environmental parameter separately. It should be noted that the types of environmental parameters and the preset environmental parameter thresholds are not limited to the above examples, and can also be set according to the actual conditions of different mining areas.
[0032] Optionally, in general, according to the preset environmental parameter threshold and the environmental parameters of each preset area of the open-pit mine, determining the environmental risk value of each preset area can be achieved in the following manner: The calculation formula of environmental risk value is: R env =ω T *R T +ω P *R P +ω D *R D , where R env represents the environmental risk value, T represents the temperature parameter of each preset area in the open-pit mine, [T min , T max ] represents the preset temperature parameter threshold, P represents the air pressure parameter of each preset area in the open-pit mine, [P min , P max ] represents the preset air pressure parameter threshold, D represents the dust concentration parameter of each preset area in the open-pit mine, [D min , D max ] represents the preset dust concentration threshold, ω TRepresents the weight coefficient of the temperature parameter, ω P Represents the weight coefficient of the air pressure parameter, ω D Represents the weight coefficient of the dust concentration parameter and satisfies ω T +ω P +ω D =1.
[0033] Here is a specific numerical example: Assume that the environmental parameters of a preset area are: Temperature T = 40 ° C, air pressure P = 0.8 atm, dust concentration D = 150 mg / m3; The preset environmental parameter thresholds are: Temperature range [T min , T max ]=[30℃,38℃], Air pressure range [P min , P max ]=[0.7atm,1.0atm], Dust concentration range [D min , D max ] = [100 mg / m3, 180 mg / m3]; The weight coefficient is set as: ω T =0.4,ω P =0.3,ω D =0.3.
[0034] Substitute into the formula to calculate: R T =(|40-(38+30) / 2|) / ((38-30) / 2)=0.8 (temperature parameter exceeds the upper limit); R P =0 (the air pressure parameter is within the preset air pressure parameter threshold range); R D =(|150-(180+100) / 2|) / ((180-100) / 2)=0.25 (dust concentration parameter exceeds the lower limit); R env =0.40.8+0.30+0.3*0.25=0.4 Therefore, the environmental risk value of this preset area is 0.4.
[0035] S102, when the environmental risk value exceeds the preset environmental risk threshold, inputting the operating parameters of the mechanical equipment in each preset area into a preset fault diagnosis model to determine whether each mechanical equipment has a fault problem; When the environmental risk value exceeds the preset environmental risk threshold, it means that the environmental conditions in the preset area may pose a threat to the normal operation of the mechanical equipment, or have caused the mechanical equipment to malfunction. The power outage system will automatically collect the operating parameters of the mechanical equipment in each preset area, such as current, voltage, temperature, speed, etc., and input them into the pre-trained fault diagnosis model to determine whether the mechanical equipment has potential faults.
[0036] The steps to build a deep learning-based fault diagnosis model are as follows: First, the power outage system collects historical operating parameter data of different mechanical equipment in multiple preset areas within the past preset time (for example, within 6 months). These operating parameters may include temperature, vibration frequency, current intensity, etc. Specifically: Temperature: The temperature record of each hour of the mechanical equipment within the past preset time collected by the power outage system.
[0037] Vibration frequency: The vibration frequency per second of the mechanical equipment collected by the power outage system within the past preset time period.
[0038] Current intensity: The current intensity record of the mechanical equipment per minute within the preset time period collected by the power outage system.
[0039] In addition, the power outage system records the equipment status (historical equipment status) of each mechanical equipment within the past preset time period, including normal operation and fault status. The historical equipment status of each mechanical equipment can be obtained through historical maintenance records or expert evaluation, which is not limited here. The power outage system stores the collected historical temperature, historical vibration frequency, historical current intensity and historical equipment status of each mechanical equipment in data set D in chronological order, and the format of each data is (historical temperature, historical vibration frequency, historical current intensity, historical equipment status). Among them, historical temperature, historical vibration frequency and historical current intensity are input features of model training, and historical equipment status is the output feature of model training.
[0040] Secondly, the power outage system performs data preprocessing on the data set D, deletes the missing data in the data set D, and normalizes the three features of historical temperature, historical vibration frequency, and historical current intensity to between 0 and 1.
[0041] Then, the power outage system builds a LSTM-based recurrent neural network, which includes an input layer, two LSTM hidden layers, a fully connected layer, and an output layer. The input layer inputs the normalized historical temperature, historical vibration frequency, and historical current intensity. The number of nodes in the hidden layer is set to 64, and the number of nodes in the fully connected layer is set to 32. The output layer outputs two results: normal operation and fault status.
[0042] Next, the power outage system uses the Adam optimizer, the learning rate is set to 0.001, and the training batch size is 32. It can also be set according to the actual situation and is not limited here. 80% of the historical data is divided into a training set and 20% is divided into a validation set. 100 epochs are trained and the model with the highest accuracy of the validation set is saved. It can also be set according to the actual situation and is not limited here. Epoch is the process in which the training data set passes through the neural network once. In machine learning and deep learning, epoch is a unit used to measure the number of times the entire training set is repeatedly learned. Specifically, when the neural network completes a forward calculation and back propagation process, that is, all data has been processed by the network once, this completes an epoch. The power outage system uses binary cross entropy as the loss function and Early Stopping to prevent overfitting. When the value of the loss function exceeds the preset function threshold, the model training is determined to be completed and the fault diagnosis model is obtained. Early Stopping is a technology in deep learning and machine learning to prevent model overfitting. It determines when to stop training by monitoring the performance of the model on the validation set.
[0043] Finally, the power outage system inputs the input features in the validation set into the fault diagnosis model, and then obtains the predicted output of the fault diagnosis model. The predicted output of the fault diagnosis model is compared with the actual output features in the validation set, and some performance indicators such as accuracy, precision, recall, F1 score, mean square error (MSE), etc. are used to evaluate the performance of the fault diagnosis model. According to the performance of the fault diagnosis model on the validation set, the parameters of the fault diagnosis model are adjusted, including adjusting the learning rate, changing the model complexity (such as increasing or decreasing the number of layers or nodes of the neural network), modifying the regularization strength, etc. This process may require multiple iterations, each of which is adjusted based on the previous learning results to optimize the fault diagnosis model.
[0044] S103, after marking the mechanical equipment with fault problems as faulty equipment, obtaining the number of faulty equipment in each preset area; The power outage system will count the number of devices determined to be faulty in each preset area, i.e., the number of faulty devices, thereby obtaining statistical information on the number of faulty devices in each preset area, which provides a basis for determining the power outage sequence based on the number of faulty devices. It should be noted that the determination and statistical method of faulty devices is not limited to the above content, and other rules can also be used to determine faulty devices, and finally obtain statistical information on faulty devices in the preset area.
[0045] S104, determining the power outage priority of each preset area according to the number of faulty devices, and sending the power outage priority to a preset power control device, so that the power control device sequentially performs power outages on the preset areas, and the more faulty devices there are, the higher the power outage priority; The power outage system can sort all preset areas from large to small according to the number of faulty equipment, and the preset area with the most faulty equipment is determined to be the area to be cut off first. For example, if preset area A has the largest number of faulty equipment, it is determined that preset area A has priority for power outage; then preset area B, and so on. It should be noted that the rules for determining the order of power outages are not limited to this example, and can also be adjusted and optimized based on factors such as area and importance. After the power outage priority is determined, the power outage system will send the power outage priority to the power control device, so that the power control device will perform power outage operations on the preset areas one by one according to the power outage priority.
[0046] S105. When it is determined that all faulty equipment in the target preset area is repaired successfully, control the power supply equipment to supply power to the target preset area.
[0047] Maintenance personnel inspect and repair faulty equipment. When a faulty device is completed, the maintenance personnel send a successful inspection message to the power outage system. When the power outage system confirms that all faulty equipment in a certain target preset area has been inspected and repaired, it is determined that the fault hidden dangers in the preset target area have been eliminated. At this time, the preset target area can be re-energized to restore power supply. The power outage system needs to maintain information exchange with the maintenance personnel to grasp the repair progress of the faulty equipment in the preset target area in real time, and ensure that power is restored only after all faulty equipment has been repaired. If a mechanical equipment fails again during the maintenance process, it needs to be re-evaluated and the power supply can be restored after it is handled.
[0048] In the above embodiment, the power outage system calculates the environmental risk value of each preset area through the environmental parameters of each preset area. When the environmental risk value exceeds the preset environmental risk threshold, it indicates that the environmental conditions of the preset area may pose a threat to the normal operation of the mechanical equipment, or have caused the mechanical equipment to fail. At this time, the power outage system will input the operating parameters of the mechanical equipment in the preset area into the preset fault diagnosis model to determine which mechanical equipment has a fault problem. The power outage system marks the mechanical equipment with a fault problem as a faulty device, and counts the number of faulty devices in each preset area. In this way, the power outage priority of each preset area is determined. The more faulty devices there are in the area, the higher the power outage priority. In order to give priority to the preset areas with more faulty devices and higher risks, so as to reduce potential losses and risks, realize targeted power outage control, and avoid losses caused by comprehensive power outages. This solution makes full use of environmental monitoring and mechanical equipment status data to realize intelligent and refined power outage decisions. Compared with traditional regular or empirical manual power outages, it can detect equipment failures in a timely manner and carry out orderly power outages, improve the pertinence of power outages and the accuracy of decision-making, reduce unnecessary production stoppage losses, and improve the safety and production efficiency of open-pit mines. When all faulty equipment in the target preset area has been repaired and confirmed to be successfully repaired, the power outage system will control the power supply equipment to restore power to the preset area. In this way, the entire process ensures that timely measures can be taken to prevent the expansion of faults in high environmental risk situations, while ensuring the smooth progress of maintenance work and the safety of workers.
[0049] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the self-diagnosis power outage method for open-pit mines in an embodiment of the present application.
[0050] S201, determining the environmental risk value of each preset area according to the preset environmental parameter threshold and the environmental parameters of each preset area of the open-pit mine; For details, please refer to step S101, which will not be described in detail here.
[0051] S202, obtaining operating parameter data of different mechanical equipment in normal operation and fault state; using the operating parameter data as input features, and using the normal operation and fault state of the mechanical equipment as output features; using the input features and the output features to train a preset model to obtain the accuracy of the preset model; when the accuracy exceeds a preset accuracy threshold, obtaining a fault diagnosis model; For details, please refer to step S102, which will not be described in detail here.
[0052] S203, when the environmental risk value is lower than the preset environmental risk threshold, generating a safety report corresponding to each preset area according to the environmental risk value and the operating parameters of the mechanical equipment in each preset area; When the environmental risk value calculated by the environmental parameters such as temperature, air pressure, and dust concentration in a preset area is lower than the preset environmental risk threshold (such as 0.5), the power outage system can collect the real-time current, speed and other operating parameters of all mechanical equipment in the preset area, and generate a safety report combining text and charts to intuitively display the operating status and environmental risk level of the mechanical equipment. Safety reports can be generated by region or for a single important mechanical equipment, and can also include content such as mechanical equipment trend analysis. The report format is not limited to a specific template and can be custom designed so that managers can intuitively view the safety status of each area or mechanical equipment. It should be noted that the generation rules of the safety report are not limited to this and can be adjusted according to specific needs.
[0053] S204, when the environmental risk value exceeds the preset environmental risk threshold, inputting the operating parameters of the mechanical equipment in each preset area into a preset fault diagnosis model to determine whether each mechanical equipment has a fault problem; For details, please refer to step S102, which will not be described in detail here.
[0054] S205, after marking the mechanical equipment with fault problems as faulty equipment, obtaining the number of faulty equipment in each preset area; For details, please refer to step S101, which will not be described in detail here.
[0055] S206, sorting all preset areas from high to low according to the number of faulty devices to obtain a power outage priority, wherein the power outage priority includes a first power outage preset area with the highest priority; Assume that an open-pit mine is divided into 5 preset areas, namely: preset area A, preset area B, preset area C, preset area D, preset area E. After faulty equipment detection and statistics, the number of faulty equipment in the 5 preset areas is: preset area A: 3 units, preset area B: 5 units, preset area C: 2 units, preset area D: 7 units, preset area E: 4 units. The power outage system will sort these 5 preset areas from high to low according to the number of faulty equipment: Preset area D: 7 units (highest priority) Preset area B: 5 units Preset area E: 4 units Preset area A: 3 units Preset area C: 2 units (lowest priority) After sorting, the power outage priority is: Preset area D (first power outage preset area) Preset Area B Preset Area E Preset Area A Preset Area C That is to say, the preset area D is determined to be the first area to be shut down because it has the largest number of faulty devices. It has the highest priority for power outage and is the first preset area for power outage. The power outage system will first shut down the preset area D according to the order of power outage priority, then shut down the preset area B, and so on, until all the faulty devices in the preset areas are repaired and power supply is gradually restored.
[0056] S207, sending the power outage priority to the power control device. When the power control device performs a power outage on the first power outage preset area at the first power outage time, a power outage reminder is issued to the first power outage preset area within the preset time before the first power outage time; following the example of step S206, the power outage system sends this power outage priority to the power control device. When the power outage is planned to be performed on the preset area D at 8 o'clock on Monday, the power outage system will issue a power outage warning to the preset area D at 7:50. The power supply to the preset area D is cut off at 8 o'clock on Monday.
[0057] S208, calculating a safe evacuation route for the first power outage preset area based on the entrance and exit location information, channel information within the area, and staff distribution information within the area, wherein the safe evacuation route is the shortest safe path from each staff member's position to the nearest entrance and exit; For the preset area A that is about to be out of power, the power outage system has obtained the coordinate information of all entrances and exits of the preset area A, the length information of each main channel, and the real-time location information of all staff members in the preset area A obtained through the GPS positioning device. The power outage system can use the Dijkstra algorithm to calculate the shortest safe evacuation path from the current position of each staff member to their nearest entrance and exit with entrances and exits as nodes and channels as edges. The safety factor of the channel needs to be comprehensively considered during the calculation process to avoid accident-prone areas. It should be noted that the area information, path planning algorithm, etc. involved in this step are only examples and do not limit this solution.
[0058] S209, sending the safe evacuation sorting route to the communication terminal in the first power outage preset area, so that the staff can evacuate according to the safe evacuation sorting route; The power outage system can display the calculated safe evacuation route in the form of a map, and send it to the communication devices held by all staff in the preset area A. The best evacuation route is displayed in real time on the interface of the communication device, and the staff is reminded to evacuate according to the displayed best evacuation route in the form of audio or vibration. When the real-time position of the staff deviates from the best evacuation route, the communication device will issue a warning. It should be noted that the specific method of sending and displaying the route is not limited to this example and can be adjusted according to the on-site situation, and is not limited here.
[0059] S210, when it is determined that all faulty equipment in the target preset area has been repaired successfully, controlling the power supply equipment to supply power to the target preset area; For details, please refer to step S101, which will not be described in detail here.
[0060] S211, judging whether the operation of each mechanical device is stable according to the startup time and real-time operation parameters of each mechanical device in the target preset area; After the power supply to the preset area A is restored, the power outage system will monitor the real-time operating parameters such as the start-up time, voltage, current, temperature, and speed of each mechanical device in the preset area A. In the embodiment of the present application, the start-up time of each mechanical device can be compared with the preset start-up time, and the real-time operating parameters of each mechanical device can be compared with the preset operating parameters. If the start-up time and real-time operating parameters of the mechanical device are both within the preset range, it means that the mechanical device is running stably. It should be noted that the specific method for judging whether the operation of each mechanical device is stable is not limited to this example, and can be adjusted according to the on-site situation, and is not limited here.
[0061] S212. When the problematic mechanical equipment is running unstably, the real-time operating parameters of the problematic mechanical equipment are input into the fault diagnosis model to determine whether to stop the operation of the problematic mechanical equipment.
[0062] If the power outage system detects that the problematic mechanical equipment ST-1213 is running unstably, the real-time temperature, real-time vibration frequency and real-time current strength of the problematic mechanical equipment ST-1213 will be automatically obtained. The real-time temperature, real-time vibration frequency and real-time current strength of the problematic mechanical equipment ST-1213 are input into the fault diagnosis model, and the fault diagnosis model outputs whether the problematic mechanical equipment ST-1213 has a fault. If there is a fault, the operation of the problematic mechanical equipment will be stopped immediately.
[0063] The following describes the power outage system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of a physical device structure of a power outage system in an embodiment of the present application.
[0064] It should be noted that Figure 3 The structure of the power outage system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.
[0065] like Figure 3As shown, the power outage system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.
[0066] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.
[0067] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 309, and / or installed from a removable medium 311. When the computer program is executed by a central processing unit (CPU) 301, various functions defined in the present invention are performed.
[0068] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.
[0069] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.
[0070] Specifically, the power outage system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the self-diagnosis power outage method for open-pit mines provided in the above embodiment is implemented.
[0071] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the power outage system described in the above embodiment; or may exist independently without being assembled into the power outage system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the power outage system, the power outage system implements the self-diagnosis power outage method for open-pit mines provided in the above embodiment.
[0072] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.
[0073] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.
[0074] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.
Claims
1. A self-diagnosis power outage method for open-pit mines, characterized in that: Applied to a power outage system, the method comprises: determining an environmental risk value of each preset area according to a preset environmental parameter threshold and environmental parameters of each preset area of an open-pit mine; When the environmental risk value exceeds a preset environmental risk threshold, the operating parameters of the mechanical equipment in each preset area are input into a preset fault diagnosis model to determine whether each mechanical equipment has a fault problem; After marking the mechanical equipment with the fault problem as a faulty device, the number of faulty devices in each preset area is obtained; the power outage priority of each preset area is determined according to the number of faulty devices, and the power outage priority is sent to a preset power supply control device, so that the power supply device sequentially performs power outages on the preset areas, and the more the number of faulty devices, the higher the power outage priority; When it is determined that all faulty equipment in the target preset area is repaired successfully, the power supply equipment is controlled to supply power to the target preset area.
2. The method according to claim 1, characterized in that Determining the environmental risk value of each preset area according to the preset environmental parameter threshold and the environmental parameters of each preset area of the open-pit mine specifically includes: The calculation formula of the environmental risk value is: R env =ω T *R T +ω P *R P +ω D *R D , Among them, R env represents the environmental risk value, T represents the temperature parameter of each preset area in the open-pit mine, [T min , T max ] represents the preset temperature parameter threshold, P represents the air pressure parameter of each preset area in the open-pit mine area, [P min , P max ] represents the preset air pressure parameter threshold, D represents the dust concentration parameter of each preset area in the open-pit mine, [D min , D max ] represents the preset dust concentration threshold, ω T Represents the weight coefficient of the temperature parameter, ω P Represents the weight coefficient of the air pressure parameter, ω D Represents the weight coefficient of the dust concentration parameter and satisfies ω T +ω P +ω D =1.
3. The method according to claim 1, characterized in that The power outage priority of each preset area is determined according to the number of faulty devices, and the power outage priority is sent to a preset power supply control device, so that the power supply device sequentially performs power outages on the preset areas. The more the number of faulty devices, the higher the power outage priority. Specifically, it includes: sorting all preset areas from high to low according to the number of faulty devices to obtain the power outage priority, and the power outage priority includes a first power outage preset area with the highest priority; The power outage priority is sent to the power control device, and when the power control device performs a power outage on the first power outage preset area at a first power outage moment, a power outage reminder is issued to the first power outage preset area within a preset time period before the first power outage moment.
4. The method according to claim 1, characterized in that: Before the step of inputting the operating parameters of the mechanical equipment in each preset area into a preset fault diagnosis model to determine whether each mechanical equipment has a fault problem when the environmental risk value exceeds the preset environmental risk threshold, the method further includes: Obtain operating parameter data of different mechanical equipment under normal operation and fault conditions; The operating parameter data is used as input features, and the normal operation and fault status of the mechanical equipment is used as output features; the input features and the output features are used to train a preset model to obtain the accuracy of the preset model; When the accuracy exceeds a preset accuracy threshold, the fault diagnosis model is obtained.
5. The method according to claim 3, characterized in that: After the step of sending the power outage priority to the power control device, when the power control device performs a power outage on the first power outage preset area at the first power outage moment, issuing a power outage reminder to the first power outage preset area within a preset time period before the first power outage moment, the method further includes: Calculate a safe evacuation route for the first power outage preset area based on the entrance and exit location information of the first power outage preset area, the channel information within the area, and the distribution information of the staff within the area, wherein the safe evacuation route is the shortest safe path from each staff position to the nearest entrance and exit; The safe evacuation route is sent to a communication terminal in the first power outage preset area, so that the staff can evacuate according to the safe evacuation route.
6. The method according to claim 1, characterized in that After the step of determining the environmental risk value of each preset area according to the preset environmental parameter threshold and the environmental parameters of each preset area of the open-pit mine, the method further includes: When the environmental risk value is lower than a preset environmental risk threshold, a safety report corresponding to each preset area is generated according to the environmental risk value and the operating parameters of the mechanical equipment in each preset area.
7. The method according to claim 1, characterized in that After the step of controlling the power supply device to supply power to the target preset area after determining that all faulty devices in the target preset area have been repaired successfully, the method further includes: According to the startup time and real-time operation parameters of each mechanical device in the target preset area, it is determined whether the operation of each mechanical device is stable; When the problematic mechanical equipment operates unstably, the real-time operating parameters of the problematic mechanical equipment are input to the fault diagnosis model to determine whether to stop the operation of the problematic mechanical equipment.
8. A power outage system, characterized in that: The power outage system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the power outage system to execute the method described in any one of claims 1-7.
9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the power outage system, the power outage system is caused to execute the method according to any one of claims 1 to 7.
10. A computer program product, characterized in that When the computer program product runs on a power outage system, the power outage system is enabled to execute the method according to any one of claims 1 to 7.