Intelligent lighting equipment maintenance management system based on data analysis

Abstract

The invention discloses an intelligent lighting equipment maintenance management system based on data analysis, and belongs to the technical field of equipment maintenance management, and the system comprises a data obtaining module which obtains associated data related to lighting equipment from a plurality of data sources; the transmission module is used for transmitting the acquired associated data to the central management platform; the central management platform carries out unified preprocessing on the associated data and then carries out analysis according to the associated data so as to judge whether the lighting equipment is abnormal or not, and the central management platform comprises a real-time judgment unit, an early warning analysis unit and a power consumption detection unit; and the maintenance adjustment module executes a corresponding strategy according to a judgment result. The power consumption condition of each lighting device can be judged, when the power consumption is abnormal, the power of the lighting device can be dynamically adjusted according to the intensity of natural light of the environment, and resources can be greatly saved under the condition that normal use of the lighting device is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of equipment maintenance management, and specifically relates to a smart lighting equipment maintenance management system based on data analysis. Background Art

[0002] Smart lighting equipment is a lighting equipment that uses advanced sensing technology, communication technology and other high-tech technologies. It achieves a comprehensive upgrade of light sources, lamps and control systems through intelligent control and management to meet users' diverse and personalized lighting needs. It is widely used in homes, offices, shopping malls, hotels, schools, hospitals, urban roads and other places.

[0003] When existing smart lighting equipment is in use, a fixed power intensity is set for lighting. However, it is affected by many factors, such as the weather. The brightness of natural light produced on rainy days and sunny days is different, and the light intensity required for lighting is also different. If lighting is performed according to a fixed power intensity, it is easy to cause a waste of resources. In addition, smart lighting equipment is generally large in number. During each routine maintenance inspection, maintenance personnel are required to conduct separate inspections on each lighting equipment, which consumes a lot of human resources and is inefficient. Summary of the invention

[0004] The purpose of the present invention is to provide a smart lighting equipment maintenance management system based on data analysis to solve the problems faced in the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A smart lighting equipment maintenance management system based on data analysis, the system comprising: A data acquisition module, the data acquisition module is used to acquire relevant data related to the lighting equipment from multiple data sources; A transmission module, the transmission module is used to transmit the acquired associated data to a central management platform; A central management platform, which performs unified preprocessing on the associated data and then performs analysis based on the associated data to determine whether the lighting equipment is abnormal. The central management platform includes a real-time judgment unit, an early warning analysis unit, and a power consumption detection unit; The real-time judgment unit is used to judge whether each lighting device has a real-time abnormal fault when working according to the acquired associated data; the early warning analysis unit is used to judge whether each lighting device has a potential abnormal risk according to the acquired associated data; the power consumption detection unit is used to judge whether the power consumption of each lighting device is normal according to the acquired associated data; A maintenance adjustment module is used to execute a corresponding strategy according to the judgment result.

[0006] Furthermore, the associated data includes current data, voltage data, resistance data, temperature data and brightness data of the lighting device itself when the lighting device is working, and also includes power consumption data of each lighting device and natural light intensity data of the environment in which the lighting device is located.

[0007] Furthermore, the working method of the real-time judgment unit is: Obtain the current value generated by each smart lighting device in real time , voltage value , resistance value R, temperature value generated during operation and the brightness value of the lighting device ; By formula Determine the fault value ; like , it is determined that the lighting device has an abnormal fault and a reminder instruction is generated; in, is the standard current value during operation, is the standard voltage value during operation, is the standard temperature value during operation, is the standard resistance value during operation, The fault threshold preset for the system. is the reference constant for the setting, and .

[0008] Furthermore, the working method of the early warning analysis unit is: When the lighting equipment is working normally, set a monitoring cycle , in this monitoring cycle In this case, the fault value parameters of lighting equipment are obtained N times, so as to formulate the curve function of the fault value of each lighting equipment changing with time. ; By formula Derive the risk index of each lighting device ; when , it is determined that the lighting device has a hidden fault risk, and a reminder instruction is generated; in, The standard curve function of the fault value of the lighting equipment set for the system changes over time, is the initial time of the monitoring cycle, is the end time of the monitoring cycle, m is the total number of lighting devices monitored in the area, and , is the change status value, and , is the fault value obtained by the lighting equipment at the jth time, and , The risk index threshold preset by the system. as well as is the proportionality coefficient.

[0009] Furthermore, the working method of the power consumption detection unit is: When no reminder instruction is generated, in the monitoring cycle Get the power consumption value of each lighting device in the area over time ; By formula Get the power consumption deviation value ; The power consumption deviation value The preset allowable deviation threshold range To compare: when When , an adjustment instruction is generated; in, It is a standard curve function of the power consumption value of the preset lighting equipment changing with time. as well as Both are allowable deviation thresholds.

[0010] Furthermore, the working method of the maintenance adjustment module is: When a reminder instruction is generated, an alarm is issued to remind the operator to perform maintenance and inspection; When an adjustment instruction is generated, the power of the lighting device is adjusted accordingly.

[0011] Furthermore, the adjustment instructions include an increase instruction and a decrease instruction: when When the height adjustment instruction is generated, the formula Adjust the power of the lighting device to ; when When the lowering instruction is generated, the formula Adjust the power of the lighting device to ; in, is the current power of the lighting equipment, The maximum power value allowed to be adjusted is is the conversion factor, is the natural light value, It is the preset natural light comparison value.

[0012] Beneficial effects of the present invention: The present invention can understand the working status of all lighting equipment in real time, so as to facilitate maintenance management personnel to handle it quickly. Moreover, since multiple parameters will affect each other when a fault occurs, comprehensive analysis of multiple parameter data can more accurately judge the status of the lighting equipment and reduce judgment errors.

[0013] The present invention combines the analysis of the difference between the fault value change of lighting equipment and the historical standard change, the difference between the fault value change of a single lighting equipment and the fault value change of all lighting equipment, and the fluctuation stability of the fault value of the lighting equipment. It can provide an early warning of the potential abnormal risks of the lighting equipment, so that corresponding countermeasures can be taken in time to reduce the occurrence of subsequent abnormal failures.

[0014] The present invention can also judge the power consumption of each lighting device. When the power consumption is abnormal, the power of the lighting device can be dynamically adjusted according to the natural light intensity of the environment, thereby maximizing resource saving while ensuring the normal use of the lighting device.

[0015] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0017] Figure 1 It is a system module block diagram of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] In one embodiment, a smart lighting equipment maintenance management system based on data analysis is disclosed. Figure 1 As shown, the maintenance management system includes: A data acquisition module, which is used to acquire relevant data related to lighting equipment from multiple data sources. The relevant data includes current data, voltage data, resistance data, temperature data and brightness data generated by the lighting equipment when it is working, as well as power consumption data of each lighting equipment and natural light intensity data of the environment in which the lighting equipment is located; A transmission module, which is used to transmit the acquired associated data to a central management platform; The central management platform performs unified preprocessing on the associated data and analyzes the associated data to determine whether the lighting equipment is abnormal. The central management platform includes a real-time judgment unit, an early warning analysis unit, and a power consumption detection unit. The real-time judgment unit is used to judge whether each lighting equipment has a real-time abnormal fault when working according to the acquired associated data; the early warning analysis unit is used to judge whether each lighting equipment has a potential abnormal risk according to the acquired associated data; and the power consumption detection unit is used to judge whether the power consumption of each lighting equipment is normal according to the acquired associated data; The maintenance and adjustment module executes corresponding strategies according to the judgment results.

[0020] Through the above technical solution, the present application can install corresponding sensors on each lighting device to obtain relevant associated data of the lighting device, such as current data, voltage data, resistance data, temperature data and brightness data generated during operation. After unified preprocessing by the central management platform, the preprocessing includes steps such as data fusion, cleaning, and standardized conversion. After processing, a real-time comprehensive analysis is performed based on data such as current value, voltage value, resistance value, temperature value and brightness value to generate a fault value, so that the lighting device is alarmed in real time according to the size of the fault value. Once an abnormality is detected, a timely alarm is issued and processed, so that the status of all lighting devices at work can be understood in real time, so that maintenance management personnel can quickly handle it; and when the lighting device does not fail, the potential abnormal risk of the lighting device is judged by the set early warning analysis unit, so that management and maintenance personnel can perform timely early warning processing to reduce the occurrence of subsequent failures and reduce property losses; at the same time, the power consumption of each lighting device is judged by the set power consumption detection unit. When it is abnormal, the power size of the lighting device can be dynamically adjusted according to the natural light intensity of the environment, and resources can be saved to the maximum while ensuring the normal use of the lighting device.

[0021] As an implementation mode of the present invention, the working method of the real-time judgment unit is: Obtain the current value generated by each smart lighting device in real time , voltage value , resistance value R, temperature value generated during operation and the brightness value of the lighting device ; By formula Get the fault value ; like , it is determined that the lighting device has an abnormal fault and a reminder instruction is generated; in, is the standard current value during operation, is the standard voltage value during operation. is the standard temperature value during operation, is the standard resistance value during operation, The fault threshold preset for the system. is the reference constant for the setting, and .

[0022] The above technical solution provides a working method of the real-time judgment unit, firstly obtaining the current value generated by each smart lighting device when it is working , voltage value , resistance value R, temperature value generated during operation and the brightness value of the lighting device Generally speaking, lighting equipment will have a relatively standard current value when it is working normally. , voltage value , resistance value R, temperature value and brightness value. When the lighting equipment fails abnormally, its corresponding data parameters will also change. Therefore, through the formula Get the fault value , it can be seen that when the brightness value is smaller, or the current value is , voltage value The greater the difference between the resistance value R and the temperature value and the standard value, the greater the possibility of abnormal failure. When the lighting equipment is abnormal, It is a fault threshold preset by the system, which is manually determined based on empirical data. In this way, the working status of all lighting equipment can be understood in real time, so that maintenance managers can handle it quickly. Since multiple parameters will affect each other when a fault occurs, comprehensive analysis of multiple parameter data can more accurately judge the status of lighting equipment and reduce judgment errors.

[0023] In the above technical solution, the standard current value during operation is , Standard voltage value during operation , Standard temperature value during operation , Standard resistance value during operation All can be determined based on the historical data of the lighting equipment, and the reference constants set And the system preset fault threshold It can be determined artificially based on experience.

[0024] The working method of the early warning analysis unit is: when the lighting equipment is working normally, set a monitoring cycle , in this monitoring cycle In this case, the fault value parameters of lighting equipment are obtained N times, so as to formulate the curve function of the fault value of each lighting equipment changing with time. ; By formula Derive the risk index of each lighting device ; when , it is determined that the lighting device has a hidden fault risk, and a reminder instruction is generated; in, The standard curve function of the fault value of the lighting equipment set for the system changes over time, is the initial time of the monitoring cycle, is the end time of the monitoring cycle, m is the total number of lighting devices monitored in the area, and , is the change status value, and , is the fault value obtained by the lighting equipment at the jth time, and , is the risk index threshold preset by the system, as well as is the proportionality coefficient.

[0025] The above technical solution provides a working method of the early warning analysis unit. First, when the lighting equipment is working normally, a monitoring cycle is set. , in this monitoring cycle In this case, the fault value parameters of lighting equipment are obtained N times, so as to formulate the curve function of the fault value of each lighting equipment changing with time. , and by the formula Derive the risk index of each lighting device ;formula It is expressed as the difference between the fault value change and the standard fault value change within the cycle, and the formula It represents the difference between the change of the fault value of a single lighting device and the change of the fault value of all lighting devices in the cycle, and the formula It indicates that the fluctuation of the fault value in this period is stable. Obviously, when the risk index The larger the value is, the higher the potential abnormal risk of the lighting equipment is. Therefore, the risk index is finally compared with the preset risk index threshold. Compare, when it appears In this way, the difference between the fault value change of the lighting equipment and the historical standard change, the difference between the fault value change of a single lighting equipment and the fault value change of all lighting equipment, and the fluctuation stability of the fault value of the lighting equipment are analyzed, which can be used to warn of the potential abnormal risks of the lighting equipment, so that corresponding countermeasures can be taken in time to reduce the occurrence of subsequent abnormal faults.

[0026] In the above technical solution, the standard curve function of the fault value of the lighting equipment set by the system over time can be formulated according to the historical operation data, and the risk index threshold value preset by the system , proportionality coefficient , And monitoring cycle The duration can be determined artificially based on empirical data and will not be elaborated on here.

[0027] The working method of the power consumption detection unit is: when no reminder instruction is generated, Get the power consumption value of each lighting device in the area over time ; By formula Get the power consumption deviation value ; The power consumption deviation value The preset allowable deviation threshold range To compare: when When , an adjustment instruction is generated; in, It is a standard curve function of the power consumption value of the preset lighting equipment changing with time. as well as All are allowable deviation thresholds; The working method of the maintenance adjustment module is: when a reminder instruction is generated, an alarm is issued to remind the operator to perform maintenance and inspection; when an adjustment instruction is generated, the power of the lighting equipment is adjusted accordingly; Adjustment instructions include raising instructions and lowering instructions: When the height adjustment instruction is generated, the formula Adjust the power of the lighting device to ; when When a reduction instruction is generated, the formula Adjust the power of the lighting device to ; in, is the current power of the lighting equipment, The maximum power value allowed to be adjusted is is the conversion factor, is the natural light value, It is the preset natural light comparison value.

[0028] The above technical solution provides a specific working method of the power consumption detection unit and a working method of the maintenance adjustment module. First, the corresponding working power is set for the lighting device according to the weather of the day, and a standard curve function of the power consumption value of the lighting device over time is formulated according to the historical data under the weather conditions. , and in the monitoring cycle Get the power consumption value of each lighting device in the area over time , through the formula Get the power consumption deviation value , the power consumption deviation value The preset allowable deviation threshold range For comparison, when When the power consumption changes, the adjustment instruction is generated; the power consumption change is compared with the standard power consumption change, so as to obtain the power consumption deviation value, and then set an allowable deviation threshold range. If it is not within the threshold range, it means that the power of the lighting equipment is abnormal and needs to be adjusted. Otherwise, no adjustment is required. When adjustment is needed, it may be that the power is insufficient and needs to be increased, or it may be that the power is too high and needs to be reduced. Therefore, when When the height adjustment instruction is generated, the formula Adjust the power of the lighting device to , it can be seen from the formula that when The larger the value, the greater the power that needs to be adjusted. The smaller the value, the more power needs to be adjusted. However, the power adjustment cannot be increased indefinitely, otherwise it will easily cause lighting equipment failure. Therefore, a maximum power value allowed for adjustment is set based on historical data. Limitations are imposed to ensure the normal operation of lighting equipment; similarly, when When the lowering instruction is generated, the formula Adjust the power of the lighting device to In this way, the power consumption of each lighting device can be judged. When the power consumption is abnormal, the power of the lighting device can be dynamically adjusted according to the natural light intensity of the environment, thereby maximizing resource conservation while ensuring the normal use of the lighting device.

[0029] It should be noted that the conversion factor , preset natural light comparison value And the preset allowable deviation threshold range The selection and determination can be made based on the historical data of the corresponding lighting equipment combined with the empirical data.

[0030] The present invention can understand the working status of all lighting equipment in real time, so as to facilitate maintenance management personnel to handle it quickly. Because multiple parameters will affect each other when a fault occurs, comprehensive analysis of multiple parameter data can more accurately judge the status of the lighting equipment and reduce the judgment error. The present invention combines the difference between the fault value change of the lighting equipment and the historical standard change, the difference between the fault value change of a single lighting equipment and the fault value change of all lighting equipment, and the fluctuation stability of the fault value of the lighting equipment for analysis. It can well warn of the potential abnormal risks of the lighting equipment, so that corresponding countermeasures can be made in time to reduce the occurrence of subsequent abnormal faults. The present invention can also judge the power consumption of each lighting device. When the power consumption is abnormal, the power of the lighting device can be dynamically adjusted according to the natural light intensity of the environment, which can maximize the saving of resources while ensuring the normal use of the lighting equipment.

[0031] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. A smart lighting equipment maintenance management system based on data analysis, characterized in that: The system comprises: A data acquisition module, the data acquisition module is used to acquire relevant data related to the lighting equipment from multiple data sources; A transmission module, the transmission module is used to transmit the acquired associated data to a central management platform; A central management platform, which performs unified preprocessing on the associated data and then performs analysis based on the associated data to determine whether the lighting equipment is abnormal. The central management platform includes a real-time judgment unit, an early warning analysis unit, and a power consumption detection unit; The real-time judgment unit is used to judge whether each lighting device has a real-time abnormal fault when working according to the acquired associated data; the early warning analysis unit is used to judge whether each lighting device has a potential abnormal risk according to the acquired associated data; the power consumption detection unit is used to judge whether the power consumption of each lighting device is normal according to the acquired associated data; A maintenance adjustment module is used to execute a corresponding strategy according to the judgment result.

2. According to claim 1, a smart lighting equipment maintenance management system based on data analysis is characterized in that: The associated data includes current data, voltage data, resistance data, temperature data and brightness data generated by the lighting device when it is working, and also includes power consumption data of each lighting device and natural light intensity data of the environment in which the lighting device is located.

3. According to claim 2, a smart lighting equipment maintenance management system based on data analysis is characterized in that: The working method of the real-time judgment unit is: Obtain the current value generated by each smart lighting device in real time , voltage value , resistance value , the temperature value generated during operation and the brightness value of the lighting device ; By formula Determine the fault value ; like , it is determined that the lighting device has an abnormal fault and a reminder instruction is generated; in, is the standard current value during operation, is the standard voltage value during operation, is the standard temperature value during operation, is the standard resistance value during operation, The fault threshold preset for the system. is the reference constant for the setting, and .

4. According to claim 3, a smart lighting equipment maintenance management system based on data analysis is characterized in that: The working method of the early warning analysis unit is: When the lighting equipment is working normally, set a monitoring cycle , in this monitoring period In this case, the fault value parameters of lighting equipment are obtained N times, so as to formulate the curve function of the fault value of each lighting equipment changing with time. ; By formula Derive the risk index of each lighting device ; when , it is determined that the lighting device has a hidden fault risk, and a reminder instruction is generated; in, The standard curve function of the fault value of the lighting equipment set for the system changes over time, is the initial time of the monitoring cycle, is the end time of the monitoring cycle, m is the total number of lighting devices monitored in the area, and , is the change status value, and , is the fault value obtained by the lighting equipment at the jth time, and , The risk index threshold preset by the system. as well as is the proportionality coefficient.

5. According to claim 4, a smart lighting equipment maintenance and management system based on data analysis is characterized in that: The working method of the power consumption detection unit is: When no reminder instruction is generated, in the monitoring cycle Get the power consumption value of each lighting device in the area over time ; By formula Get the power consumption deviation value ; The power consumption deviation value The preset allowable deviation threshold range To compare: when When , an adjustment instruction is generated; in, It is a standard curve function of the power consumption value of the preset lighting equipment changing with time. as well as Both are allowable deviation thresholds.

6. The data analysis-based intelligent lighting equipment maintenance management system according to claim 5, characterized in that: The working method of the maintenance adjustment module is: When a reminder instruction is generated, an alarm is issued to remind the operator to perform maintenance and inspection; When an adjustment instruction is generated, the power of the lighting device is adjusted accordingly.

7. The data analysis-based intelligent lighting equipment maintenance management system according to claim 6, characterized in that: The adjustment instructions include an increase instruction and a decrease instruction: when When the height adjustment instruction is generated, the formula Adjust the power of the lighting device to ; when When the lowering instruction is generated, the formula Adjust the power of the lighting device to ; in, is the current power of the lighting equipment, The maximum power value allowed to be adjusted is is the conversion factor, is the natural light value, It is the preset natural light comparison value.

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