System and method for administrating equipment by diagnising power measuring sensor data

Abstract

The present invention relates to a system and method for managing facility operation through the analysis of power measurement sensor data. The system comprises: a power pattern prediction unit that outputs usage status information indicating whether the facility to which the power measurement sensor is attached is in a stopped, standby, or operating state based on power amount information transmitted from the power measurement sensor; a facility status determination unit that determines facility status information of the facility to which the power measurement sensor is attached based on power amount information transmitted from the power measurement sensor; and a control unit that generates final status information of the facility based on the usage status information of the facility transmitted from the power pattern prediction unit and the facility status information transmitted from the facility status determination unit, and outputs the generated final status information through a dashboard.

Description

Technology Field

[0001] The present invention relates to a system and method for managing equipment operation through the analysis of power measurement sensor data. More specifically, it relates to a system and method for managing equipment operation through the analysis of power measurement sensor data that learns various power data patterns generated during equipment operation and provides efficient manufacturing equipment management through real-time monitoring that visualizes various information of the equipment based on this learning. Background Technology

[0003] Various equipment operated by electricity, such as motors and cutting machines, has a problem in that it is difficult to check their operating status from a remote location.

[0004] Meanwhile, due to the recent advancements in IoT sensors and related technologies, it has become possible to acquire diagnostic and equipment maintenance data using them. Furthermore, research is underway on various methodologies capable of deriving meaningful results through big data and AI analysis. Consequently, there is a demand for technology that applies these techniques to power-consuming equipment, enabling the convenient monitoring of the equipment's operating status simply by attaching power measurement sensors. The problem to be solved

[0006] The present invention aims to solve the aforementioned problems by providing a system and method for managing equipment operation through power measurement sensor data analysis, which learns various power data patterns generated during equipment operation and provides efficient manufacturing equipment management through real-time monitoring that visualizes various information of the equipment based on this.

[0007] In particular, another objective of the present invention is to eliminate the need for complex installation processes for existing facilities by attaching only power measurement sensors to various electrically operated facilities, to provide real-time monitoring of the operation of various facilities based on power consumption information detected by the power measurement sensors, and to enable efficient operation of facilities through analysis of real-time operating status and energy consumption. means of solving the problem

[0009] To solve the problem described above, the present invention provides an equipment operation management system through power measurement sensor data analysis, comprising: a power pattern prediction unit that outputs usage status information indicating whether the equipment to which the power measurement sensor is attached is in a stopped, standby, or operating state based on power amount information transmitted from the power measurement sensor; an equipment status determination unit that determines equipment status information of the equipment to which the power measurement sensor is attached based on power amount information transmitted from the power measurement sensor; and a control unit that generates final status information of the equipment based on the usage status information of the equipment transmitted from the power pattern prediction unit and the equipment status information transmitted from the equipment status determination unit, and outputs the generated final status information through a dashboard.

[0010] Here, the power measurement sensor is mounted on an electrically operated facility to detect power consumption information of the facility and can transmit the detected power consumption information to at least one of the power pattern prediction unit, the facility status determination unit, and the control unit.

[0011] In addition, the power pattern prediction unit may be implemented as an artificial intelligence-based model that learns power usage patterns by taking power amount information and status information of the equipment transmitted from the power measurement sensor as input.

[0012] Additionally, the power pattern prediction unit may include: a preprocessing unit that performs preprocessing on input power amount information and transmits it to a learning unit and a power pattern prediction model; a learning unit that inputs power amount information, which is learning data for power pattern prediction, and status information of equipment corresponding to the power amount information into the power pattern prediction model to train the power pattern prediction model; and a power pattern prediction model that is trained by the power amount information of the equipment and the status information of the equipment, and outputs usage status information indicating whether the equipment is in a stopped, standby, or operating state based on the power amount information of a specific equipment transmitted from a power measurement sensor.

[0013] In addition, the learning unit can train a power pattern prediction model based on power amount information detected repeatedly at preset time intervals according to the stopped state, standby state, and operating state of the equipment in which the power measurement sensor is installed.

[0014] In addition, the learning unit can check basic power consumption information when the equipment is in a stopped state, check standby power consumption information when the equipment is in a standby state when power is supplied (Power on), and then check operating power consumption information when the equipment is in an operating state (Operation), while repeating this process at preset intervals, input power consumption information according to each state information of the equipment into a power pattern prediction model and train the power pattern prediction model.

[0015] In addition, the learning execution unit can calculate an average value for power consumption information based on the respective status information of the equipment, set this as a threshold, and then transmit the set threshold to the equipment status judgment unit.

[0016] In addition, the equipment status determination unit can check a threshold, determine whether it is in an operating or standby state, determine that it is in a stopped state if the threshold is less than the operating threshold and the standby threshold, determine that it is in an operating or standby state if it is in an operating or standby state, determine that it is in an operating or standby state if it is in a state that lasts for more than a preset time, otherwise determine that it is in a stopped state, and repeat the process of returning to the initial state and checking the threshold again, thereby generating equipment status information of the equipment and transmitting it to the control unit.

[0017] According to another aspect of the present invention, a method for managing facility operation through power measurement sensor data analysis is provided, comprising: a first step of outputting usage status information indicating whether the facility to which the power measurement sensor is attached is in a stopped, standby, or operating state based on power amount information transmitted from the power measurement sensor; a second step of determining facility status information of the facility to which the power measurement sensor is attached based on power amount information transmitted from the power measurement sensor; and a third step of generating final status information of the facility based on the usage status information of the facility in the first step and the facility status information in the second step, and outputting the generated final status information through a dashboard. Effects of the invention

[0019] According to the present invention, a system and method for managing equipment operation through power measurement sensor data analysis can be provided, which learns various power data patterns generated during equipment operation and provides efficient manufacturing equipment management through real-time monitoring that visualizes various information of the equipment based thereon.

[0020] In particular, the present invention eliminates the need for complex installation processes for existing equipment by attaching only power measurement sensors to various electrically operated facilities, and enables real-time monitoring of the operation of various facilities based on power consumption information detected by the power measurement sensors, thereby allowing for efficient operation of facilities through analysis of real-time operating status and energy consumption. Brief explanation of the drawing

[0022] FIG. 1 is a diagram showing the overall configuration and connection relationships of an equipment operation management system (100) through power measurement sensor data analysis according to an embodiment of the present invention. Figure 2 shows an example of power amount information measured by a power measurement sensor (200). Figure 3 shows an example of a power pattern prediction unit (10). FIG. 4 is a flowchart for explaining the operation of the learning execution unit (12). Figure 5 is a flowchart showing the operation of the equipment status judgment unit (20). Figure 6 shows an example of a screen of a dashboard (300). FIGS. 7 to 11 show other examples of the screen of the dashboard (300). Specific details for implementing the invention

[0023] Hereinafter, embodiments according to the present invention will be described in detail with reference to the attached drawings.

[0024] FIG. 1 is a diagram showing the overall configuration and connection relationships of an equipment operation management system (100) through power measurement sensor data analysis according to an embodiment of the present invention.

[0025] Referring to FIG. 1, the facility operation management system (100, hereinafter simply referred to as "system (100)") through power measurement sensor data analysis of the present embodiment includes a power pattern prediction unit (10), a facility status determination unit (20), and a control unit (30).

[0026] In addition, although not described, it includes a database for storing data used in the present invention.

[0027] A power measurement sensor (200) is mounted on various equipment that is operated by electricity, such as a wire cutter, various motors, a lathe, etc., detects power consumption information of the equipment, and transmits the detected power consumption information to at least one of a power pattern prediction unit (10), an equipment status determination unit (20), and a control unit (30).

[0028] Figure 2 shows an example of power amount information measured by a power measurement sensor (200).

[0029] Referring to FIG. 2, it can be seen that power amount information detected by a power measurement sensor (200) mounted on a wire cutting machine is detected over time.

[0030] This power amount information is transmitted to the power pattern prediction unit (10), the equipment status determination unit (20), and the control unit (30).

[0031] The power pattern prediction unit (10) performs the function of outputting usage status information indicating whether the equipment is in a stopped, standby, or operating state based on the power amount information of the equipment transmitted from the power measurement sensor (200).

[0032] To this end, the power pattern prediction unit (10) can be implemented as an artificial intelligence-based model that learns power usage patterns by taking as input the power amount information of the equipment and the status information of the equipment transmitted from the power measurement sensor (200).

[0033] Figure 3 shows an example of a power pattern prediction unit (10).

[0034] Referring to FIG. 3, the power pattern prediction unit (10) includes a preprocessing unit (11), a learning execution unit (12), and a power pattern prediction model (13).

[0035] The preprocessing unit (11) is a means for performing preprocessing on input power amount information and transmitting it to the learning execution unit (12) and the power pattern prediction model (13).

[0036] Here, preprocessing refers to a procedure for converting and processing input power information into data that can be used for learning and classification in a power pattern prediction model (13) through processing such as parsing.

[0037] The learning execution unit (12) performs the function of inputting learning data for power pattern prediction into the power pattern prediction model (13) to train the power pattern prediction model (13).

[0038] Here, the training data may be power amount information that has been preprocessed in the preprocessing unit (11) and status information of the equipment corresponding to the power amount.

[0039] The learning execution unit (12) can train a power pattern prediction model (13) based on power amount information detected repeatedly at preset time intervals (e.g., 30 minutes) according to each of the stopped state, standby state, and operating state of the equipment in which the power measurement sensor (200) is installed.

[0040] FIG. 4 is a flowchart for explaining the operation of the learning execution unit (12).

[0041] Referring to FIG. 4, first, basic power consumption information is checked when the equipment is in a stopped state, and when power is supplied (Power on) and the equipment is in a standby state, standby power consumption information is checked. Subsequently, when the equipment is in an operating state (Operation), operating power consumption information is checked. While repeating this process at a preset cycle (e.g., every 30 minutes), power consumption information (basic power consumption information, standby power consumption information, operating power consumption information) according to each state information (stopped state, standby state, operating state) of the equipment is input into a power pattern prediction model (13) and the power pattern prediction model (13) is trained.

[0042] Additionally, the learning execution unit (12) can calculate the average value of the power consumption information (basic power consumption information, standby power consumption information, operating power consumption information) according to each state information (stopped state, standby state, operating state) of the equipment, and set this as a threshold. The set threshold is transmitted to the equipment state judgment unit (20).

[0043] The power pattern prediction model (13) is learned by the power amount information of the equipment and the status information of the equipment, and performs the function of outputting usage status information indicating whether the equipment is in a stopped, standby, or operating state based on the power amount information of the specific equipment transmitted from the power measurement sensor (200).

[0044] This power pattern prediction model (13) can be implemented as a machine learning-based neural network model, and conventional machine learning models such as CNN, RNN, AE, etc. can be used. Since the machine learning-based neural network model itself is known by prior art and is not the direct purpose of the present invention, a detailed description is omitted here.

[0045] The power pattern prediction model (13), after completing learning using the learning data (equipment status information and power amount information based on the status information) input by the learning execution unit (12) as described above, outputs equipment status information corresponding to the power amount information when power amount information transmitted from the power measurement sensor (200) is input, and transmits this to the control unit (30).

[0046] The equipment status determination unit (20) performs the function of determining the equipment status information of the equipment to which the power measurement sensor (200) is attached based on the power amount information transmitted from the power measurement sensor (200).

[0047] Figure 5 is a flowchart showing the operation of the equipment status judgment unit (20).

[0048] Referring to FIG. 5, first, the equipment status determination unit (20) checks the threshold and determines whether it is in an operating or standby state (S100, S110).

[0049] For example, if the power consumption information is above the operating threshold, it is determined to be in an operating state, and if it is above the standby threshold, it is determined to be in a standby state.

[0050] In this case, if the operating threshold and standby threshold are lower than the operating threshold, it is determined to be in a stopped state (S120).

[0051] If the state is in operation or standby mode, if the state persists for a preset time (e.g., 30 minutes) or longer, it is determined to be in operation or standby mode (S130, S140, S150); otherwise, it is determined to be in a stopped state and returns to the initial state to check the threshold (S140, S100).

[0052] Here, each threshold is transmitted from the learning execution unit (12) as described above.

[0053] The equipment status determination unit (20) generates equipment status information of the equipment through the above process and transmits the generated equipment status information to the control unit (30).

[0054] The control unit (30) performs the function of managing and controlling the overall operation of the system (100). In particular, in the present invention, the control unit (30) generates final state information of the equipment based on the equipment usage state information transmitted from the power pattern prediction unit (10) and the equipment state information transmitted from the equipment state judgment unit (20), and performs the function of outputting the generated final state information through the dashboard (300).

[0055] The control unit (30) can generate final state information of the equipment by using only one of the equipment usage state information transmitted from the power pattern prediction unit (10) and the equipment state information transmitted from the equipment state judgment unit (20). Of course, it is also possible to use both.

[0056] The dashboard (300) is an interface displayed through the display unit of the manager terminal, and the manager can efficiently determine the operating status of the equipment to which the power measurement sensor (200) is attached through the dashboard (300).

[0057] Figure 6 shows an example of a screen of a dashboard (300).

[0058] Referring to FIG. 6, it can be seen that the overall operational status of the equipment can be monitored and the real-time operation status is displayed. At this time, the operation status is the status information determined by the control unit (30) based on the status information transmitted from the power management prediction unit (10) and the equipment status judgment unit (20) as described above, and it can be seen that it is displayed by being classified into a stopped state, a standby state, and an operating state. In addition, it can be displayed together as a list of the overall equipment.

[0059] Figure 7 shows another example of the screen of the dashboard (300).

[0060] Referring to Fig. 7, it can be seen that the detailed status of each facility is displayed.

[0061] In other words, it can be seen that for each facility, facility information, status information, KPI status, operating hours, power consumption comparison table, electrical parameters, and electrical quality parameters are provided on a single screen.

[0062] FIGS. 8 and FIGS. 9 show another example of a screen of a dashboard (300).

[0063] Referring to Figures 8 and 9, the operating status of each piece of equipment is displayed as a timeline chart, and an alarm is triggered when a problem occurs so that the manager can quickly recognize and respond to it.

[0064] Figure 10 shows another example of a screen of a dashboard (300).

[0065] Figure 10 is a screen displaying the overall power consumption status and the maximum peak time period, through which the manager can grasp the overall energy operation status and check real-time power status, the rate of fluctuation compared to the previous day, and statistical information by time period. In addition, the maximum power amount status and the active power peak status can be checked through the active power peak status.

[0066] Figure 11 shows another example of a screen of a dashboard (300).

[0067] Figure 11 shows an overall statistical and analysis report, which is a screen that provides an equipment operation analysis report based on collected data.

[0068] As shown in Fig. 11, the overall operating rate of the facility and the status of power consumption can be checked, and by providing a ranking of the facility operating rates, the facility utilization plan can be modified or relocated according to the operating rate.

[0069] In addition, by providing power usage statistics, it enables checking the ranking and power usage of each facility.

[0070] Although embodiments according to the present invention have been described above, the present invention is not limited to the above embodiments, and it is obvious that various modifications and variations are possible. Explanation of the symbols

[0072] 100...Facility operation management system through power measurement sensor data analysis 200...power measurement sensor 300...dashboard 10...Power pattern prediction unit 11...Preprocessing section 12...Learning Performance Unit 13...Power pattern prediction model 20...Equipment Status Judgment Unit 30...Control unit

Claims

Claim 1 A facility operation management system through the analysis of power measurement sensor data, comprising: a power pattern prediction unit that outputs usage status information indicating whether the facility to which the power measurement sensor is attached is in a stopped, standby, or operating state based on power amount information transmitted from the power measurement sensor; a facility status determination unit that determines facility status information of the facility to which the power measurement sensor is attached based on power amount information transmitted from the power measurement sensor; and a control unit that generates final status information of the facility based on the facility usage status information transmitted from the power pattern prediction unit and the facility status information transmitted from the facility status determination unit, and outputs the generated final status information through a dashboard, wherein the power pattern prediction unit is implemented as an artificial intelligence-based model that learns power usage patterns by taking power amount information of the facility and status information of the facility transmitted from the power measurement sensor as inputs, and the power pattern prediction unit comprises: a preprocessing unit that performs preprocessing on the input power amount information and transmits it to a learning execution unit and a power pattern prediction model; and a learning execution unit that inputs power amount information and facility status information corresponding to the power amount information, which are learning data for power pattern prediction, into the power pattern prediction model to train the power pattern prediction model.A system for managing equipment operation through analysis of power measurement sensor data, comprising a power pattern prediction model that learns from power consumption information of the equipment and status information of the equipment, and outputs usage status information indicating whether the equipment is in a stopped, standby, or operating state based on power consumption information of a specific piece of equipment transmitted from a power measurement sensor; wherein the learning execution unit calculates an average value for power consumption information according to each state information of the equipment, sets this as a threshold, and transmits the set threshold to an equipment status determination unit; wherein the equipment status determination unit checks the threshold, determines whether it is in an operating or standby state, determines that it is in a stopped state if the threshold is less than the operating threshold and standby threshold, determines that it is in an operating or standby state if it is in an operating or standby state, determines that it is in an operating or standby state if it persists for more than a preset time, otherwise determines that it is in a stopped state, and repeats the process of returning to an initial state and checking the threshold again, thereby generating equipment status information of the equipment and transmitting it to a control unit. Claim 2 A facility operation management system through power measurement sensor data analysis according to claim 1, wherein the power measurement sensor is mounted on a facility operated by electricity, detects power amount information of the facility, and transmits the detected power amount information to at least one of the power pattern prediction unit, the facility status determination unit, and the control unit. Claim 3 delete Claim 4 delete Claim 5 A facility operation management system through power measurement sensor data analysis according to claim 1, wherein the learning performing unit learns a power pattern prediction model based on power amount information detected repeatedly at preset time intervals according to each of the stopped state, standby state, and operating state of the facility in which the power measurement sensor is installed. Claim 6 A system for managing equipment operation through power measurement sensor data analysis according to claim 5, wherein the learning unit checks basic power consumption information when the equipment is in a stopped state, checks standby power consumption information when the equipment is in a standby state when power is supplied (Power on), and subsequently checks operating power consumption information when the equipment is in an operating state (Operation), while repeating the process at preset intervals, inputting power consumption information according to each state information of the equipment into a power pattern prediction model and training the power pattern prediction model. Claim 7 delete Claim 8 delete Claim 9 A method for managing facility operation through analysis of power measurement sensor data comprises: a first step of outputting usage status information indicating whether the facility to which the power measurement sensor is attached is in a stopped, standby, or operating state based on power amount information transmitted from the power measurement sensor; a second step of determining facility status information of the facility to which the power measurement sensor is attached based on power amount information transmitted from the power measurement sensor; and a third step of generating final status information of the facility based on the facility usage status information of the first step and the facility status information of the second step, and outputting the generated final status information through a dashboard. The first step is performed by a power pattern prediction unit implemented as an artificial intelligence-based model that learns power usage patterns by taking power amount information of the facility and status information of the facility transmitted from the power measurement sensor as inputs. The power pattern prediction unit includes: a preprocessing unit that performs preprocessing on the input power amount information and transmits it to a learning unit and a power pattern prediction model; and a learning unit that inputs power amount information and facility status information corresponding to the power amount information, which are learning data for power pattern prediction, into the power pattern prediction model to train the power pattern prediction model.A method for managing equipment operation through analysis of power measurement sensor data, characterized by including a power pattern prediction model that learns from power consumption information of equipment and status information of said equipment, and outputs usage status information indicating whether said equipment is in a stopped, standby, or operating state based on power consumption information of a specific piece of equipment transmitted from a power measurement sensor; wherein the learning execution unit calculates an average value for power consumption information according to each state information of the equipment, sets this as a threshold, and transmits the set threshold to an equipment status determination unit; wherein the equipment status determination unit checks the threshold, determines whether it is in an operating or standby state, determines that it is in a stopped state if the threshold is less than the operating threshold and the standby threshold, determines that it is in an operating or standby state if it is in an operating or standby state, determines that it is in an operating or standby state if it persists for more than a preset time, otherwise determines that it is in a stopped state, returns to an initial state, and repeats the process of checking the threshold again to generate equipment status information of the equipment.

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