OPS power supply state detection system and control method

Abstract

The invention discloses an OPS power supply state detection system and a control method, relates to the technical field of OPS power supplies, and solves the technical problems of power consumption increase or equipment failure and the like caused by lack of intelligent management of the OPS power supply in the prior art. Operation data are monitored in real time, the relation between output power and load power is analyzed according to the condition of the operation data, and the energy consumption rate of an OPS module in an analysis period is evaluated; when abnormity occurs, a corresponding abnormal signal is sent to the power supply control module, and whether unstored data exists is analyzed; if yes, storing the data and then cutting off the power supply; if not, directly cutting off the power supply; the intelligent level of power management of the OPS module is improved, and the energy efficiency ratio and the operation stability of equipment are remarkably improved through effective power state detection and automatic control.

Description

Technical Field

[0001] The invention belongs to the field of OPS power supplies, and in particular relates to an OPS power supply state detection system and a control method. Background Art

[0002] OPS (Open Pluggable Specification) is a standardized digital signage interface specification jointly developed by Intel and display manufacturers. The internal components of OPS are a mini PC with X86 architecture, using Intel Core processor, equipped with memory, hard disk, multiple input and output interfaces and Windows operation interface. OPS computer or OPS module is an open pluggable computer module, also a microcomputer, which can be plugged in and out to make the overall layout beautiful. It is widely used in electronic devices such as all-in-one computers, electronic whiteboards, digital signage, etc.

[0003] At present, the research on OPS modules mainly focuses on the anti-hot plug aspect, because OPS modules usually do not have hot plug functions, and electronic devices do not have protection devices for hot plugging of OPS modules. It is easy to cause misoperation when hot plugging the OPS modules, causing damage to the OPS modules. Therefore, the existing technology mainly focuses on the research of hot plug protection devices, but ignores the monitoring of the power status of the OPS modules during operation, and the power management lacks intelligence, resulting in increased power consumption or equipment failure.

[0004] Therefore, the present invention provides an OPS power supply status detection system and control method. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an OPS power supply status detection system and a control method, which are used to solve the technical problems that the prior art lacks intelligent management of the OPS power supply, resulting in increased power consumption or equipment failure.

[0006] To achieve the above object, a first aspect of the present invention provides an OPS power status detection system, comprising an analysis module, and an information acquisition module and a power control module connected thereto;

[0007] Information collection module: used to collect the operation data of the OPS module;

[0008] Analysis module: used to determine whether the operation data is within the corresponding preset threshold range; if yes, the operation data is normal; if no, the operation data is abnormal, and an operation data abnormality signal is sent to the power control module; and,

[0009] When the operating data is normal, analyze whether the power output by the OPS module meets the load power requirement; if yes, the OPS module works normally; if not, generate a power shortage signal and send it to the power control module;

[0010] When the OPS module works normally within the analysis period, it is determined whether the energy consumption rate of the OPS module within the analysis period is abnormal; if yes, an energy consumption abnormality signal is sent to the power supply control module; if no, the OPS module works normally;

[0011] Power control module: used to determine whether there is any unsaved data when receiving an abnormal signal; if yes, save the data and then cut off the power; if not, cut off the power directly; among which, the abnormal signal includes abnormal operation data signal, insufficient power signal and abnormal energy consumption signal.

[0012] Preferably, the operating data includes input / output current and input / output voltage.

[0013] Preferably, the collecting of the operation data of the OPS module includes:

[0014] Analyze whether the OPS module is in the on state, detect the input / output current through the current detection device, and detect the input / output voltage through the voltage detection device;

[0015] The detection position of input current and input voltage is set at the connection point between the OPS module and the power supply;

[0016] The detection position of the output current and the output voltage is set at the connection point between the output interface of the OPS module and the load.

[0017] The present invention detects the input / output current and voltage of the OPS module in real time to understand the actual working parameters of the OPS module, such as the stability of the current and voltage, and the system can immediately detect any abnormal fluctuations or deviations from the preset range. This real-time monitoring mechanism helps to quickly identify potential power failures or performance degradation problems, so that preventive measures can be taken in advance to avoid damage or shutdown of equipment due to power supply problems, greatly improving the stability and reliability of the system; and when the OPS module fails, detailed operating data can provide strong support for troubleshooting. By comparing the data changes before and after the failure, the problem can be quickly located, the fault diagnosis time can be reduced, and the maintenance efficiency can be improved. In addition, the long-term accumulated operating data can also provide a basis for formulating preventive maintenance plans, further reducing the occurrence of failures.

[0018] Preferably, the analyzing whether the OPS module is in an on state includes:

[0019] Connect the factory-set OPS module to the integrated device, and after concluding that the OPS module is in the shutdown state based on the absence of a signal in the OPS channel, obtain the level value of the power state detection interface and assign the level value of the power state detection interface to the power on / off state attribute value set by the system;

[0020] According to the level value of the power status detection interface and the power on / off attribute value, the current state of the OPS module is obtained; if it is in the on state, no processing is performed; if it is in the off state, the OPS module is switched from the off state to the on state.

[0021] The process of the present invention greatly improves the intelligence level of the system and realizes the automatic management of the power on and off of the OPS module. The state of the OPS module can be accurately judged without manual intervention, and it can be automatically started when necessary, reducing the operation and maintenance cost and improving work efficiency; when the OPS module is detected to be in the shutdown state, the system can immediately identify and respond through the level value of the power state detection interface, and quickly switch the OPS module from the shutdown state to the startup state, ensuring the continuity and efficiency of the all-in-one device and avoiding system delays or failures caused by the failure to start the OPS module.

[0022] Preferably, the preset threshold range of the analysis operation data includes:

[0023] Extract the operation data of several OPS modules when they are operating abnormally from the historical data; arrange the operation data from small to large, extract the minimum and maximum values ​​in the operation data, perform mean processing, and obtain the median of the operation data;

[0024] The operating data is divided into two groups with the median as the boundary, and marked as a small operating data group and a large operating data group respectively; the maximum value in the small operating data group and the minimum value in the large operating data group are analyzed to obtain a preset range of the operating data.

[0025] Preferably, the step of analyzing the maximum value in the small operation data group and the minimum value in the large operation data group to obtain a preset range of the operation data includes:

[0026] By formula C i =A i -A i-1 Calculate the A in the small running data group i , A i-1 The difference between the two data C i ; Judge C i Is it greater than the preset difference? If yes, the data after the ith one in the small operation data group is classified as the large operation data group; if no, the small operation data is retained; where A i is the i-th running data in the small running data group, A i-1is the i-1th operation data in the small operation data group; i is the data sequence number in the small operation data group, i=0, 1, 2, ..., n, n is a positive integer;

[0027] When the small run data set does not change, the large run data set is analyzed;

[0028] By formula D j =B j+1 -B j Calculate the B in the large operation data group j , B j+1 The difference between the two data D j ; Judge D j Is it greater than the preset difference? If yes, the data after the jth data in the small operation data group are classified as the small operation data group; if no, they are retained; wherein, B j is the jth running data in the large running data group, B j+1 is the j+1th operation data in the large operation data group; j is the data sequence number in the large operation data group, j=0, 1, 2, ..., m, m is a positive integer;

[0029] The maximum value is extracted from the processed small operation data group, and the minimum value is extracted from the large operation data group. The minimum value and the maximum value constitute a preset threshold range of the operation data.

[0030] The present invention divides the data set into small operation / large operation data groups by the median value, which is convenient for analyzing the difference between the two groups of data, extracting the part of the small or large operation data group that is greater than the preset difference, and obtaining a new small / large operation data group. By extracting the maximum value from the processed small operation data group and the minimum value from the large operation data group, the maximum value and the minimum value constitute the preset threshold range of the operation data. This threshold setting method takes into account both the overall distribution of the data and the local characteristics of the data, making the threshold more reasonable and effective, while reducing unnecessary calculations and improving the efficiency of data processing. This advantage is more obvious when processing large-scale data sets. It provides a reliable reference standard for subsequent data monitoring, anomaly detection, etc.

[0031] Preferably, when the operating data is normal, analyzing whether the power output by the OPS module meets the load power requirement includes:

[0032] The output power Po of the OPS module is calculated by the formula Po=Uo×Io, and it is judged whether the output power of the OPS module is greater than the power required by the load and less than the rated power of the load; if so, the power output of the OPS module meets the power requirement of the load; if not, the power output of the OPS module does not meet the power requirement of the load.

[0033] Preferably, several instantaneous powers when the OPS module is operating normally are extracted from the historical data, and averaged to obtain the power required by the load.

[0034] The present invention can obtain the current power supply capacity of the OPS module in real time and accurately by directly calculating the output power Po. The measurement method based on the actual voltage Uo and current Io is more accurate and reliable, ensuring the accuracy of the judgment result. Secondly, by comparing the output power of the OPS module with the power required by the load and the rated power of the load, it can comprehensively evaluate whether the power supply capacity of the OPS module can meet the basic operating requirements of the load without exceeding the load's tolerance range. This dual judgment standard effectively avoids unstable load operation due to insufficient power or energy waste and potential safety hazards caused by excess power; and,

[0035] The power required by the load is determined by extracting the instantaneous power of the OPS module during normal operation from the historical data and performing average processing. This method makes full use of the value of historical data, making the setting of the load power demand more scientific and reasonable. It can not only reflect the average power demand of the load under normal working conditions, but also reduce the impact of instantaneous fluctuations or abnormal data on the judgment results, thereby improving the robustness of the judgment.

[0036] Preferably, when the OPS module works normally within the analysis period, evaluating the energy consumption rate of the OPS module within the analysis period includes:

[0037] The analysis period is divided into several sub-periods of equal duration, and the mean values ​​of the input / output currents in the sub-periods are calculated, marked as EIr and EIo, respectively, and the mean values ​​of the input / output voltages are marked as EUr and EUo, respectively;

[0038] The energy consumption rate NHL of OPS in the sub-period is calculated by the formula NHL=(EPI-EPO) / EPI; wherein, EPI is the average input power in the sub-period, EPI=EUr×EIr; EPO is the average output power in the sub-period, EPO=EUo×EIo.

[0039] Preferably, the determining whether the energy consumption rate of the OPS module within the analysis period is abnormal includes:

[0040] According to the energy consumption rate of the sub-period, establish the energy consumption rate curve of the OPS module in the analysis period;

[0041] The energy consumption curve and the standard energy consumption curve are set in the same coordinate system. When the energy consumption rate curve fluctuates around the standard energy consumption curve, the energy consumption is normal; otherwise, the energy consumption is abnormal.

[0042] The present invention subdivides the analysis period into several sub-periods of equal duration, and respectively calculates the mean values ​​of the input / output current and voltage in these sub-periods, thereby obtaining the average input power and average output power in the sub-periods, as well as the energy consumption rate calculated by them. By subdividing the analysis period, the energy consumption characteristics of the OPS module in different time periods can be captured more meticulously, which helps to discover possible instantaneous or local energy consumption anomalies, thereby improving the sensitivity and accuracy of energy consumption monitoring; and by establishing an energy consumption rate curve and comparing and analyzing it with a standard energy consumption curve, it is possible to intuitively determine whether the energy consumption of the OPS module in the entire analysis period is normal, and can quickly identify energy consumption anomalies, thereby providing strong support for subsequent troubleshooting and performance optimization.

[0043] Preferably, when an abnormal signal is received, determining whether there is currently running data includes:

[0044] Obtain the running task feature information from the background, save the current data and close it according to the task feature information; wherein the task feature information includes the task type and task status.

[0045] Preferably, the power control module also counts the number of occurrences of abnormal signals within the operating cycle, marked as YC; the failure probability Q per unit time is calculated by the formula Q=YC / TZ; the service life of the OPS module is analyzed based on the failure probability per unit time; wherein TZ is the operating cycle length.

[0046] Preferably, analyzing the service life of the OPS module according to the failure probability per unit time includes:

[0047] The failure probability per unit time of several continuous operation cycles is extracted, and a failure probability curve is established. When the failure probability curve shows an upward trend, the service life of the OPS module is gradually reduced, and a new OPS module needs to be replaced in time.

[0048] The present invention calculates the failure probability per unit time, can accurately reflect the probability of failure of the OPS module per unit time, and fits the failure probability of continuous operation cycles to obtain a failure probability curve. By analyzing the curve development trend of the failure probability, the remaining life of the OPS module can be discovered earlier, and the OPS module that is about to reach the service life limit can be replaced in time, thereby avoiding unplanned downtime and improving the reliability and stability of the system.

[0049] Preferably, the horizontal axis of the failure probability curve is the number of the operation cycle, that is, the operation cycles are marked in chronological order, and the vertical axis is the failure probability per unit time.

[0050] Preferably, an OPS power state control method comprises the following steps:

[0051] Step 1: Collecting the operating data of the OPS module; wherein the operating data includes input / output current and input / output voltage;

[0052] Step 2: Determine whether the operating data is within the corresponding preset threshold range; if yes, the operating data is normal; and proceed to step 3; if no, the operating data is abnormal, and proceed to step 5;

[0053] Step 3: When the operating data is normal, analyze whether the power output by the OPS module meets the load power requirement; if yes, the OPS module works normally and proceeds to step 4; if no, the power is abnormal and proceeds to step 5;

[0054] Step 4: When the OPS module works normally during the analysis period, the energy consumption rate of the OPS module during the analysis period is evaluated; whether the energy consumption rate of the OPS module during the analysis period is abnormal; if yes, proceed to step 5; if no, the OPS module works normally;

[0055] Step 5: When an abnormality occurs, determine whether there is currently unsaved data; if yes, save the data and then cut off the power; if not, cut off the power directly; wherein the abnormal signals include abnormal operation data, abnormal power and abnormal energy consumption.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. The present invention extracts a number of abnormal historical operation data from historical data, divides the historical operation data into small / large operation data groups according to the median value, extracts part of the data in the small or large operation data group that is greater than a preset difference, and obtains a new small / large operation data group. By extracting the maximum value from the processed small operation data group and the minimum value from the large operation data group, the preset threshold range corresponding to the operation data is obtained; this method considers both the overall distribution of the data and the local characteristics of the data, making the threshold more reasonable and effective, and providing a reliable reference standard for subsequent data monitoring, anomaly detection, etc.;

[0058] 2. The present invention has designed a comprehensive data protection and power cut-off mechanism. After receiving an abnormal signal, it first determines whether there is any unsaved data to ensure the safety of important data and not to lose it, and then performs the power cut-off operation, thereby avoiding the risk of data loss and system damage, and further improving the security and stability of the system. In summary, the present invention has shown significant advantages in improving equipment operation efficiency, ensuring data security, and achieving energy conservation and emission reduction.

[0059] 3. The present invention compares the operation data with the corresponding preset threshold range; when the operation data is normal, analyzes whether the power output by the OPS module meets the load power demand; if yes, the OPS module works normally; if not, sends a power shortage signal to the power control module; if the operation data is abnormal, sends an operation data abnormal signal to the power control module; and, when the OPS module works normally within the analysis period, evaluates the energy consumption rate of the OPS module within the analysis period; if the energy consumption rate is abnormal, sends an energy consumption abnormal signal to the power control module; when the power control module receives the abnormal signal, if there is unsaved data, saves the data and then cuts off the power; if not, directly cuts off the power; by analyzing the operation data, output power and energy consumption, etc., comprehensively monitors the power status of the OPS module, and performs automatic control, so as to improve the energy efficiency and stability of the equipment based on intelligent power management. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0062] Figure 2 A schematic diagram of a method for analyzing a threshold range of operating data according to the present invention;

[0063] Figure 3 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0064] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. 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.

[0065] See also Figure 1 , the first aspect of the present invention provides an OPS power status detection system, including an analysis module, and an information acquisition module and a power control module connected thereto;

[0066] The information acquisition module acquires the operation data of the OPS module; wherein the operation data includes input / output current and input / output voltage.

[0067] Specifically, step S1: analyzing the current state of the OPS module and starting the OPS module;

[0068] Connect the factory-set OPS module to the integrated device, and after concluding that the OPS module is in the shutdown state based on the absence of a signal in the OPS channel, obtain the level value of the power state detection interface and assign the level value of the power state detection interface to the power on / off state attribute value set by the system;

[0069] According to the level value of the power status detection interface and the power on / off attribute value, the current state of the OPS module is obtained; if it is in the on state, no processing is performed; if it is in the off state, the OPS module is switched from the off state to the on state.

[0070] Step 2: When the OPS module is in the on state, the current detection device detects the input / output current, and the voltage detection device detects the input / output voltage.

[0071] The detection position of the input current and the input voltage is set at the connection point between the OPS module and the power supply;

[0072] The detection position of the output current and the output voltage is set at the connection point between the output interface of the OPS module and the load.

[0073] It should be noted that the load is a device connected to the OPS module, such as a display, that is, teaching equipment used for teaching and conferencing, and the premise for connecting the OPS module with each display device is interface matching.

[0074] The analysis module determines whether the operation data is within the corresponding preset threshold range; if yes, the operation data is normal; if no, the operation data is abnormal, and sends an operation data abnormality signal to the power control module;

[0075] See also Figure 2 , analyze the preset threshold range of running data, including:

[0076] Extract the operation data of several OPS modules when they are operating abnormally from the historical data; arrange the operation data from small to large, extract the minimum and maximum values ​​in the operation data, perform mean processing, and obtain the median of the operation data;

[0077] The operating data is divided into two groups with the median as the boundary, and marked as a small operating data group and a large operating data group respectively; the maximum value in the small operating data group and the minimum value in the large operating data group are analyzed to obtain a preset range of the operating data.

[0078] It should be noted that the small running data group is the data set on the left side of the median, and the large running data group is the data set on the right side of the median.

[0079] By formula C i =Ai -A i-1 Calculate the A in the small running data group i , A i-1 The difference between the two data C i ; Judge C i Is it greater than the preset difference? If yes, the data after the ith one in the small operation data group is classified as the large operation data group; if no, the small operation data is retained; where A i is the i-th running data in the small running data group, A i-1 is the i-1th operation data in the small operation data group; i is the data sequence number in the small operation data group, i=0, 1, 2, ..., n, n is a positive integer;

[0080] When the small operation data group has not changed, the large operation data group is analyzed; wherein, the analysis order may also be changed, and the large operation data group may be analyzed first and then the small operation data group;

[0081] By formula D j =B j+1 -B j Calculate the B in the large operation data group j , B j+1 The difference between the two data D j ; Judge D j Is it greater than the preset difference? If yes, the data after the jth data in the small operation data group are classified as the small operation data group; if no, they are retained; wherein, B j is the jth running data in the large running data group, B j+1 is the j+1th operation data in the large operation data group; j is the data sequence number in the large operation data group, j=0, 1, 2, ..., m, m is a positive integer;

[0082] The maximum value is extracted from the processed small operation data group, and the minimum value is extracted from the large operation data group. The minimum value and the maximum value constitute a preset threshold range of the operation data.

[0083] For example: Taking abnormal current data as an example, assuming that its small operation data group is (A0, A1, ... A i-1 , A i ,…,A n-1 ,A n ), because the running data is divided by the median value, the part of the data association between the two data groups is in the middle part of the data, so the small running data group is operated from the largest data to the smallest data, and A is calculated in sequence n -A n-1 =C n , A n-1 -A n-2 =C n-1 , …, Ai -A i-1 =C i ,…,A1-A0=C1, if we calculate to A i -A i-1 =C i , and C i If it is greater than the difference threshold, the subsequent calculation is stopped, and A i The operation data after that are classified into the large operation data group, that is, the small operation data group (A i ,…,A n-1 ,A n ) is divided into its large operation data group, then the large operation data group increases the group of data;

[0084] If the differences obtained after the small operation data group is calculated are all less than or equal to the difference threshold, the large operation data group is analyzed. Assume that the large operation data group is (B0, B1, ... B i-1 , B i ,…,B n-1 ,B n ), from the above analysis, it can be seen that the large operation data group performs difference calculation from the smallest data to the largest data, and calculates B1-B0=D0, B2-B1=D1, ..., B i+1 -B i =D i , …, B m -B m-1 =D m-1 , if we calculate B i+1 -B i =D i , and D i If it is greater than the difference threshold, the subsequent calculation is stopped, and B i The operation data before and after are classified into a large operation data group, that is, the large operation data group (B0,…,B i-1 ,B i ) is divided into a small operation data group, then the small operation data group increases the group of data;

[0085] If after the large operating data group is calculated, the differences obtained are all less than or equal to the difference threshold, they are all retained; after the data group division is completed, the maximum value in the small operating data group and the minimum value in the large operating data group are extracted to obtain the preset threshold range of the operating data.

[0086] It should be noted that the preset threshold range of each operating data is analyzed separately according to the above method.

[0087] And, when the operating data is normal, analyze whether the power output by the OPS module meets the load power requirement; if yes, the OPS module works normally; if not, send a power shortage signal to the power control module;

[0088] Specifically, several instantaneous powers of the OPS module during normal operation are extracted from historical data and averaged to obtain the power required by the load;

[0089] The output power Po of the OPS module is calculated by the formula Po=Uo×Io, and it is judged whether the output power of the OPS module is greater than the power required by the load and less than the rated power of the load; if so, the power output of the OPS module meets the power requirement of the load; if not, the power output of the OPS module does not meet the power requirement of the load.

[0090] It should be noted that when the operating data is normal, it is possible that the current output power cannot meet the power required by the current load operation, which will cause the load to fail to work normally. Therefore, when the operating data is normal, further judge the output power situation and evaluate whether the OPS module is operating normally.

[0091] When the OPS module works normally within the analysis period, the energy consumption rate of the OPS module within the analysis period is evaluated; whether the energy consumption rate of the OPS module within the analysis period is abnormal is determined; if yes, an energy consumption abnormality signal is generated and sent to the power supply control module; if no, the OPS module works normally;

[0092] Specifically, the analysis period is divided into several sub-periods of equal duration, and the mean values ​​of the input / output currents in the sub-periods are calculated, which are marked as EIr and EIo, respectively, and the mean values ​​of the input / output voltages are marked as EUr and EUo, respectively;

[0093] The energy consumption rate NHL of OPS in the sub-period is calculated by the formula NHL=(EPI-EPO) / EPI; wherein, EPI is the average input power in the sub-period, EPI=EUr×EIr; EPO is the average output power in the sub-period, EPO=EUo×EIo.

[0094] The present invention evaluates the power loss degree of the OPS module during operation through the energy consumption rate; the power loss degree is mainly closely related to the input power and the output power; if the input power is large and the output power is small, the power lost during operation is large, and the power loss rate relative to the input power is large, indicating that the power loss degree is more serious, that is, the energy consumption rate value is large; if the input power is small and the output power is large, the power lost during operation is small, and the power loss rate relative to the input power is small, indicating that the power loss degree is lighter, that is, the energy consumption rate value is small.

[0095] According to the energy consumption rate of the sub-period, establish the energy consumption rate curve of the OPS module in the analysis period;

[0096] The energy consumption curve and the standard energy consumption curve are set in the same coordinate system. When the energy consumption rate curve fluctuates around the standard energy consumption curve, the energy consumption is normal; otherwise, the energy consumption is abnormal.

[0097] Among them, the changing trends of the energy consumption rate curve include the following situations:

[0098] When the energy consumption rate curve is in an upward / downward trend and some areas exceed / fall below the standard energy consumption curve, energy consumption anomaly occurs;

[0099] When the energy consumption rate curve is above or below the standard energy consumption curve, energy consumption abnormality occurs;

[0100] When the energy consumption rate curve fluctuates around the standard energy consumption curve, the energy consumption is normal.

[0101] Power control module: used to determine whether there is any unsaved data when receiving an abnormal signal; if yes, save the data and then cut off the power; if not, cut off the power directly; among which, the abnormal signal includes abnormal operation data signal, insufficient power signal and abnormal energy consumption signal.

[0102] Specifically, the characteristic information of the task being run is obtained from the background, and the current data is saved and closed according to the characteristic information of the task; wherein the characteristic information of the task includes the task type and the task status.

[0103] It should be noted that the background will display the tasks being executed by the OPS module, and evaluate whether to save the data based on the characteristics of the task. If a program such as MS OFFICE is being executed and is in editing status, the data will be saved. If a social program is being executed, the data does not need to be saved because social programs can receive information even when they are offline, unless the information is deleted by the user.

[0104] The power control module also counts the number of abnormal signal occurrences during the operation cycle, marked as YC; the failure probability per unit time Q is calculated by the formula Q=YC / TZ; the service life of the OPS module is analyzed based on the failure probability per unit time; where TZ is the length of the operation cycle.

[0105] The present invention evaluates the probability of failure of the OPS module per unit time through the failure probability assessment. The probability of failure per unit time is mainly closely related to the number of occurrences of abnormal signals in the operation cycle and the duration of the operation cycle. When the number of occurrences of abnormal signals in a shorter operation cycle is large, it indicates that the probability of failure is high, that is, the OPS module fails more frequently and the failure probability is large.

[0106] The failure probability per unit time of several consecutive operating cycles is extracted, and a failure probability curve is established; wherein the horizontal axis of the failure probability curve is the number of the operating cycle, that is, the operating cycles are marked in chronological order, and the vertical axis is the failure probability per unit time.

[0107] When the failure probability curve keeps an upward trend, which means that the possibility of failure occurring in a unit time is getting bigger and bigger, the service life of the OPS module is gradually reduced and a new OPS module needs to be replaced in time.

[0108] See also Figure 3 The second aspect of the present invention provides an OPS power state control method, comprising:

[0109] Step 1: Collecting the operating data of the OPS module; wherein the operating data includes input / output current and input / output voltage;

[0110] Step 2: Determine whether the operating data is within the corresponding preset threshold range; if yes, the operating data is normal; and proceed to step 3; if no, the operating data is abnormal, and proceed to step 5;

[0111] Step 3: When the operating data is normal, analyze whether the power output by the OPS module meets the load power requirement; if yes, the OPS module works normally and proceeds to step 4; if no, the power is abnormal and proceeds to step 5;

[0112] Step 4: When the OPS module works normally during the analysis period, the energy consumption rate of the OPS module during the analysis period is evaluated; whether the energy consumption rate of the OPS module during the analysis period is abnormal; if yes, proceed to step 5; if no, the OPS module works normally;

[0113] Step 5: When an abnormality occurs, determine whether there is currently unsaved data; if yes, save the data and then cut off the power; if not, cut off the power directly; wherein the abnormal signals include abnormal operation data, abnormal power and abnormal energy consumption.

[0114] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0115] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An OPS power status detection system, characterized in that: It includes an analysis module, and an information acquisition module and a power control module connected thereto; Information collection module: used to collect the operation data of the OPS module; Analysis module: used to determine whether the operating data is within the corresponding preset threshold range; if yes, the operating data is normal; if no, the operating data is abnormal, and an operating data abnormality signal is sent to the power control module; as well as, When the operating data is normal, analyze whether the power output of the OPS module meets the load power requirement; if yes, the OPS module works normally; If not, an insufficient power signal is generated and sent to the power control module; When the OPS module works normally during the analysis period, it is determined whether the energy consumption rate of the OPS module during the analysis period is abnormal; if yes, an energy consumption abnormality signal is sent to the power control module; No, the OPS module works normally; Power control module: used to determine whether there is any unsaved data when receiving an abnormal signal; if yes, save the data and then cut off the power; if not, cut off the power directly; among which, the abnormal signal includes abnormal operation data signal, insufficient power signal and abnormal energy consumption signal.

2. An OPS power status detection system according to claim 1, characterized in that: The operation data includes input / output current and input / output voltage.

3. An OPS power supply status detection system according to claim 2, characterized in that: The operation data of the OPS module is collected, including: Analyze the current status of the OPS module, turn on the OPS module, detect the input / output current through the current detection device, and detect the input / output voltage through the voltage detection device; The detection position of input current and input voltage is set at the connection point between the OPS module and the power supply; The detection position of the output current and the output voltage is set at the connection point between the output interface of the OPS module and the load.

4. An OPS power supply status detection system according to claim 3, characterized in that: The analyzing the current state of the OPS module and starting the OPS module includes: Connect the factory-set OPS module to the integrated device, and after concluding that the OPS module is in the shutdown state based on the absence of a signal in the OPS channel, obtain the level value of the power state detection interface and assign the level value of the power state detection interface to the power on / off state attribute value set by the system; According to the level value of the power status detection interface and the power on / off attribute value, the current state of the OPS module is obtained; if it is in the on state, no processing is performed; if it is in the off state, the OPS module is switched from the off state to the on state.

5. An OPS power supply status detection system according to claim 1, characterized in that: Analyzes the preset threshold ranges of operation data, including: Extract the operation data of several OPS modules when they are operating abnormally from the historical data; arrange the operation data from small to large, extract the minimum and maximum values ​​in the operation data, perform mean processing, and obtain the median of the operation data; The operating data is divided into two groups with the median as the boundary, and marked as a small operating data group and a large operating data group respectively; the maximum value in the small operating data group and the minimum value in the large operating data group are analyzed to obtain a preset range of the operating data.

6. An OPS power supply status detection system according to claim 5, characterized in that: The step of analyzing the maximum value in the small operation data group and the minimum value in the large operation data group to obtain the preset range of the operation data includes: By formula C i =A i -A i-1 Calculate the A in the small running data group i , A i-1 The difference between the two data C i ; Judge C i Is it greater than the preset difference? If yes, the data after the ith one in the small operation data group is classified as the large operation data group; if no, the small operation data is retained; where A i is the i-th running data in the small running data group, A i-1 is the i-1th operation data in the small operation data group; i is the data sequence number in the small operation data group, i=0, 1, 2, ..., n, n is a positive integer; When the small run data set does not change, the large run data set is analyzed; By formula D j =B j+1 -B j Calculate the B in the large operation data group j , B j+1 The difference between the two data D j ; Judge D j Is it greater than the preset difference? If yes, the data after the jth data in the small operation data group are classified as the small operation data group; if no, they are retained; wherein, B j is the jth running data in the large running data group, B j+1 is the j+1th operation data in the large operation data group; j is the data sequence number in the large operation data group, j=0, 1, 2, ..., m, m is a positive integer; The maximum value is extracted from the processed small operation data group, and the minimum value is extracted from the large operation data group. The minimum value and the maximum value constitute a preset threshold range of the operation data.

7. An OPS power supply status detection system according to claim 1, characterized in that: When the operating data is normal, analyzing whether the power output by the OPS module meets the load power requirement includes: The output power Po of the OPS module is calculated by the formula Po=Uo×Io, and it is judged whether the output power of the OPS module is greater than the power required by the load and less than the rated power of the load; if so, the power output of the OPS module meets the power requirement of the load; if not, the power output of the OPS module does not meet the power requirement of the load.

8. An OPS power supply status detection system according to claim 7, characterized in that: Several instantaneous powers of the OPS module during normal operation are extracted from the historical data and averaged to obtain the power required by the load.

9. An OPS power supply status detection system according to claim 1, characterized in that: When the OPS module works normally during the analysis period, evaluating the energy consumption rate of the OPS module during the analysis period includes: The analysis period is divided into several sub-periods of equal duration, and the mean values ​​of the input / output currents in the sub-periods are calculated, marked as EIr and EIo, respectively, and the mean values ​​of the input / output voltages are marked as EUr and EUo, respectively; The energy consumption rate NHL of OPS in the sub-period is calculated by the formula NHL=(EPI-EPO) / EPI; wherein, EPI is the average input power in the sub-period, EPI=EUr×EIr; EPO is the average output power in the sub-period, EPO=EUo×EIo.

10. An OPS power supply status detection system according to claim 9, characterized in that: The determining whether the energy consumption rate of the OPS module in the analysis period is abnormal includes: According to the energy consumption rate of the sub-period, establish the energy consumption rate curve of the OPS module in the analysis period; The energy consumption curve and the standard energy consumption curve are set in the same coordinate system. When the energy consumption rate curve fluctuates around the standard energy consumption curve, the energy consumption is normal; otherwise, the energy consumption is abnormal.

11. An OPS power supply status detection system according to claim 1, characterized in that: When an abnormal signal is received, determining whether there is currently running data includes: Obtain the running task feature information from the background, save the current data and close it according to the task feature information; wherein the task feature information includes the task type and task status.

12. An OPS power supply status detection system according to claim 9, characterized in that: The power control module also counts the number of abnormal signal occurrences during the operation cycle, marked as YC; the failure probability per unit time Q is calculated by the formula Q = YC / TZ; The service life of the OPS module is analyzed based on the failure probability per unit time; where TZ is the operating cycle length.

13. An OPS power supply status detection system according to claim 12, characterized in that: The analyzing the service life of the OPS module according to the failure probability per unit time includes: The failure probability per unit time of several continuous operation cycles is extracted, and a failure probability curve is established. When the failure probability curve shows an upward trend, the service life of the OPS module is gradually reduced, and a new OPS module needs to be replaced in time.

14. An OPS power supply status detection system according to claim 13, characterized in that: The horizontal axis of the failure probability curve is the number of the operating cycle, that is, the operating cycles are marked in chronological order, and the vertical axis is the failure probability per unit time.

15. An OPS power state control method, based on an OPS power state detection system according to any one of claims 1 to 14, characterized in that: The following steps are involved: Step 1: Collecting the operating data of the OPS module; wherein the operating data includes input / output current and input / output voltage; Step 2: Determine whether the operating data is within the corresponding preset threshold range; if yes, the operating data is normal; and proceed to step 3; if no, the operating data is abnormal, and proceed to step 5; Step 3: When the operating data is normal, analyze whether the power output by the OPS module meets the load power requirement; if yes, the OPS module works normally and proceeds to step 4; if no, the power is abnormal and proceeds to step 5; Step 4: When the OPS module works normally during the analysis period, the energy consumption rate of the OPS module during the analysis period is evaluated; whether the energy consumption rate of the OPS module during the analysis period is abnormal; if yes, proceed to step 5; if no, the OPS module works normally; Step 5: When an abnormality occurs, determine whether there is currently unsaved data; if yes, save the data and then cut off the power; if not, cut off the power directly; wherein the abnormal signals include abnormal operation data, abnormal power and abnormal energy consumption.

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