WO2017088354A1 - 设备故障诊断方法、装置及*** - Google Patents

设备故障诊断方法、装置及*** Download PDF

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Publication number
WO2017088354A1
WO2017088354A1 PCT/CN2016/081297 CN2016081297W WO2017088354A1 WO 2017088354 A1 WO2017088354 A1 WO 2017088354A1 CN 2016081297 W CN2016081297 W CN 2016081297W WO 2017088354 A1 WO2017088354 A1 WO 2017088354A1
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Prior art keywords
smart device
signal strength
data
smart
change rate
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PCT/CN2016/081297
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English (en)
French (fr)
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张泽
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张泽
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Publication of WO2017088354A1 publication Critical patent/WO2017088354A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0221—Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/24—Pc safety
    • G05B2219/24048—Remote test, monitoring, diagnostic

Definitions

  • the present invention relates to the field of Internet of Things, and in particular to a device fault diagnosis method, apparatus and system.
  • IoT devices and smart home devices generally do not have the function of fault diagnosis. For some key devices, such as smart door locks and access control systems, if a failure occurs, the user experience will be seriously affected. Affect the personal safety of the user. Therefore, how to quickly detect the occurrence of a fault and how to predict the possibility of a potential fault is of great significance to the user of the device.
  • a part of the door lock system is equipped with a sensor or a micro switch to monitor a specific part of the door lock, thereby functioning as a fault detection.
  • the above methods can detect a single type of fault and the alarm is not timely. Therefore, the existing smart home equipment cannot provide reliable fault detection function, and it is impossible to diagnose and predict the fault of the current operating condition of the equipment.
  • a small number of smart home devices have fault detection functions, the devices that can be detected have a single fault and cannot provide fault alarms to users in real time.
  • the embodiment of the invention provides a device fault diagnosis method, device and system, so as to at least solve the technical problem that the user experience is poor due to the failure to detect and alarm the fault of the smart home device.
  • a smart device fault diagnosis method includes: establishing a communication connection with a smart device; acquiring, by using a communication connection, operation data of the smart device, where the operation data includes at least: a communication connection Signal strength and/or battery voltage of the smart device; diagnoses whether the smart device has failed based on the operational data of the smart device.
  • acquiring the running data of the smart device by using the communication connection includes: receiving the running data sent by the smart device according to the preset first time interval; and feeding back the acknowledgement signal corresponding to the running data to the smart device.
  • obtaining the running data of the smart device through the communication connection further comprising: acquiring and receiving the smart The receiving time of the running data sent by the device; determining the second time interval between the current system time and the receiving time according to the receiving time and the current system time; comparing the second time interval with a preset time threshold to determine the smart device Whether a failure has occurred.
  • whether the smart device is faulty according to the running data of the smart device includes: generating a signal strength record corresponding to the smart device according to the received signal strength according to the chronological order; recording according to the signal strength And determining a signal strength mean value of the signal strength; determining that the smart device has a communication failure when the received signal strength and the signal strength mean signal strength difference are greater than a preset first threshold.
  • whether the smart device is faulty according to the operating data of the smart device includes: generating, according to the received battery voltage, a battery voltage record corresponding to the smart device according to a time sequence; according to the battery voltage Recording, calculating a current voltage change rate of the current battery voltage of the smart device; comparing the voltage difference between the current voltage change rate and the preset average voltage change rate with a preset second threshold value, and diagnosing whether the smart device is faulty.
  • the method for determining the average voltage change rate includes: acquiring a current voltage change rate of the smart device; acquiring an average voltage change rate of the smart device in a normal operation state; and calculating a new average according to the current voltage change rate and the average voltage change rate; Voltage change rate.
  • the operation data further includes: an ambient temperature, wherein the voltage difference between the current voltage change rate and the preset average voltage change rate is compared with a preset second threshold, and whether the smart device is diagnosed to be faulty includes: The ambient temperature corrects the second threshold to obtain a third threshold for determining whether the smart device has a hardware failure. When the voltage difference exceeds the third threshold, it is determined that the smart device has a hardware failure.
  • the method further includes: after determining that the smart device is faulty, generating alarm information corresponding to the fault.
  • the running data further includes: a smart device ID, a password input record, and an operation record.
  • a smart device fault diagnosis apparatus including: a connection module, configured to establish a communication connection with the smart device; and an acquisition module, configured to acquire the operation of the smart device by using a communication connection Data, wherein the operation data includes at least: a signal strength of the communication connection and/or a battery voltage of the smart device; and a diagnosis module configured to diagnose whether the smart device has failed according to the operation data of the smart device.
  • the obtaining module includes: a sub-receiving module, configured to receive the running data sent by the smart device according to the preset first time interval; and the sub-transmission module, configured to feed back the acknowledgement signal corresponding to the running data to the smart device.
  • the obtaining module further includes: a sub-acquisition module, configured to acquire a receiving time of receiving the running data sent by the smart device; and a first sub-determining module, configured to determine the current system time and the receiving time according to the receiving time and the current system time.
  • the second time interval between the second time interval is used to compare the second time interval with a preset time threshold to determine whether the smart device has failed.
  • the device further includes: a prompting module, configured to generate alarm information corresponding to the fault after determining that the smart device is faulty.
  • a smart device fault diagnosis system including: an intelligent device, configured to send operation data according to a preset time interval; and a wireless gateway, wirelessly connected with the smart device, for establishing A communication connection between the server and the smart device; the server is connected to the wireless gateway, and is configured to obtain the running data of the smart device through the wireless gateway, and diagnose whether the smart device is faulty according to the running data of the smart device.
  • a communication connection with the smart device is established; and the operation data of the smart device is acquired through the communication connection, wherein the operation data at least includes: a signal strength of the communication connection and/or a battery voltage of the smart device;
  • the operation data of the device and the way to diagnose whether the smart device has failed have achieved the purpose of monitoring the working state of the smart device, thereby realizing the technical effect of using the monitored operational data to predict the failure of the smart device, and further The technical problem of poor user experience due to failure to detect and alarm the malfunction of the smart home device is solved.
  • FIG. 1 is a schematic diagram of a smart device fault diagnosis system according to an embodiment of the present invention.
  • FIG. 2 is a flowchart of a smart device fault diagnosis method according to an embodiment of the present invention.
  • FIG. 3 is a flowchart of a smart device fault diagnosis method in practical application according to an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a smart device fault diagnosis apparatus according to an embodiment of the present invention.
  • FIG. 5 is a schematic diagram of an optional device for fault diagnosis of a smart device according to an embodiment of the invention.
  • FIG. 1 is a schematic diagram of a smart device fault diagnosis system according to an embodiment of the present invention.
  • the smart device fault diagnosis system includes: The smart device 10, the wireless gateway 20, and the server 30.
  • the smart device 10 is configured to send operation data according to a preset time interval; the wireless gateway 20 is wirelessly connected to the smart device 10, and is used to establish a communication connection between the server 30 and the smart device 10; the server 30, and the wireless gateway The connection is 20 for acquiring the operation data of the smart device 10 through the wireless gateway 20, and diagnosing whether the smart device 10 has failed according to the operation data of the smart device 10.
  • the communication data established with the smart device can be used to obtain the running data of the smart device in operation in real time.
  • the diagnosis of the running status of the smart device is realized by the parameters of the acquired running data and the changes.
  • the purpose of monitoring the working state of the smart device is achieved, thereby realizing the technical effect of using the monitored running data to predict the fault of the smart device.
  • the technical problem of poor user experience due to failure to detect and alarm the malfunction of the smart home device is solved.
  • the smart device has a wireless communication module, and the smart device can communicate with the wireless gateway through the wireless communication module and connect to the server in the Internet through the wireless gateway; the wireless communication module can record the wireless signal between the smart device and the wireless gateway. strength.
  • the smart device is also capable of recording the real-time voltage value of the battery used.
  • the smart device communicates with the wireless gateway at a fixed time interval. During each handshake communication, the smart device sends wireless signal strength and voltage value to the server, and the Internet server records the wireless signal strength and voltage value, and diagnoses the smart device through calculation. Whether it is malfunctioning.
  • An embodiment of an intelligent device fault diagnosis method is provided according to an embodiment of the present invention.
  • the steps illustrated in the flowchart of the figures may be performed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, may differ from this The steps shown are performed in the order shown or described.
  • FIG. 2 is a flowchart of a smart device fault diagnosis method according to an embodiment of the present invention. As shown in FIG. 2, the method includes the following steps:
  • Step S102 establishing a communication connection with the smart device.
  • Step S104 Acquire operation data of the smart device by using a communication connection, where the operation data at least includes: a signal strength of the communication connection and a battery voltage of the smart device.
  • Step S106 Diagnose whether the smart device has a fault according to the running data of the smart device.
  • step S102 to step S106 the running data of the smart device in operation can be obtained in real time by using the communication connection established with the smart device.
  • the diagnosis of the running status of the smart device is realized by the parameters of the acquired running data and the changes.
  • connection manner used in the step of establishing a communication connection with the smart device may be a wired connection or a wireless connection.
  • wired connection has the advantages of stable transmission, simple structure, etc., but due to its complicated wiring, the initial cost is high.
  • Establishing a communication connection by means of wireless connection can solve the wiring problem well, and can be realized by using WIFI, Bluetooth, mobile communication network and the like.
  • the specific connection method can be determined according to actual needs, and no specific limitation is made here.
  • step S104 may include:
  • Step S41 Receive operation data sent by the smart device according to a preset first time interval.
  • step S43 an acknowledgement signal corresponding to the operational data is fed back to the smart device.
  • the running data of the smart device may be acquired by using the communication method of the handshake communication through the foregoing steps S41 to S43.
  • the smart device sends the running data to the server according to the preset first time interval.
  • the server After receiving the running data sent by the smart terminal, the server returns an acknowledgement signal for receiving the running data to the smart device.
  • a smart lock is taken as an example for description.
  • the smart lock can be connected to the wireless gateway through wireless communication, and further connected to the server in the Internet through the wireless gateway.
  • the smart lock communicates with the Internet server at a preset time interval (receives a piece of server feedback data after sending a piece of communication data), so that the server can timely acquire the online state and running state of the smart lock.
  • the information of the handshake communication sent by the smart lock may include: the ID of the smart lock, the wireless signal strength of the smart lock, the battery voltage value of the smart lock, the password input condition of the smart lock, the swipe of the smart lock, and the handle of the smart lock.
  • the action record, etc., the server can record all the handshake communication data sent by the smart lock, and generate a wireless signal strength curve and a battery voltage curve according to the wireless signal strength and the battery voltage value.
  • the server may also send the data request signal to the smart device according to the preset first time frequency, and the smart device returns to the current after receiving the data request.
  • the server may also send the data request signal to the smart device according to the preset first time frequency, and the smart device returns to the current after receiving the data request. The way the intelligent device runs data is implemented.
  • the foregoing steps may further include:
  • Step S45 Acquire a receiving time of receiving the running data sent by the smart device.
  • Step S47 determining a second time interval between the current system time and the receiving time according to the receiving time and the current system time.
  • step S49 the second time interval is compared with a preset time threshold to determine whether the smart device has failed.
  • the receiving time when receiving the running data sent by the smart device is acquired through step S45 to step S49, and the second time between the current system time and the last received running data is determined according to the receiving time and the current system time. interval.
  • the second time interval is compared with a preset time threshold to determine whether the smart device has failed by using the comparison result of the second time interval and the time threshold.
  • the threshold can be determined according to the actual network environment. Of course, it can also be determined according to the first time interval.
  • a smart lock is also taken as an example for description. If the server cannot receive the handshake communication data sent from the smart lock for a certain period of time, it can directly determine the communication failure. For example, the smart lock can be set to initiate a handshake communication every 20-40 seconds. If the server does not receive the handshake communication data sent by the smart lock within a predetermined time, the server can diagnose that the smart lock has a communication failure, wherein the time can be It is the communication interval, which is an integral multiple of the first time interval. For example, the set time is 5 communication intervals. It is set according to the actual situation, and no specific restrictions are made here.
  • the server can calculate the average strength of the smart lock wireless signal, and obtain the real-time obtained signal strength and average signal. The intensity is compared. If the current signal strength is lower than the average signal strength by more than a preset threshold, it is determined to be a communication failure; the server calculates the voltage falling speed according to the battery voltage curve, when the battery voltage falling speed is greater than a preset threshold. , to determine the smart lock failure.
  • the above method can detect the abnormal condition in time by monitoring the working state of the smart device, and can notify the customer to perform the maintenance process in time.
  • step S106 when the running data is the signal strength, in step S106, according to the running data of the smart device, whether the smart device is faulty may include:
  • Step S61 according to the received signal strength, generate a signal strength record corresponding to the smart device in chronological order.
  • Step S62 determining the signal strength mean of the signal strength according to the signal strength record.
  • Step S63 when the signal strength difference between the received signal strength and the signal strength mean is greater than a preset first threshold, determining that the smart device has a communication failure.
  • the smart lock is taken as an example for description.
  • the smart lock contains wireless signal strength information in each handshake communication message.
  • the server can use the received wireless signal strength information to calculate the average signal strength for a certain period of time. For example, the average signal strength within 1-24 hours before the current time can be calculated to obtain the signal strength mean.
  • the current signal strength is compared with the signal strength average. If the current signal strength is lower than the signal strength mean value exceeds a preset first threshold, the smart lock can be diagnosed to have a communication failure.
  • the first threshold may also be a ratio.
  • the smart lock may be diagnosed to have a communication failure.
  • the current signal strength may be the signal strength included in the latest handshake communication information, or may be the average of the signal strengths included in the latest 5-10 handshake communication information, preferably using the most recently received predetermined number of signal strengths. The average value, so as to avoid the probability of occurrence of false alarm failure due to the occasional decrease in signal strength.
  • the signal strength of the wireless connection between them should be relatively stable due to the relatively fixed position of the smart lock and the gateway under normal working conditions. If the signal strength drops sharply at a certain moment, although the smart lock can still maintain normal communication and normal operation, the state of this signal below the normal value is likely to be due to the communication circuit, antenna and other components of the smart lock. Caused by an abnormality. More serious communication failures may occur at any time.
  • the operational data in the diagnosis of whether the smart device has failed, may include:
  • Step S64 generating a battery voltage record corresponding to the smart device in chronological order according to the received battery voltage.
  • Step S65 calculating a current voltage change rate of the current battery voltage of the smart device according to the battery voltage record.
  • step S66 the voltage difference between the current voltage change rate and the preset average voltage change rate is compared with a preset second threshold to diagnose whether the smart device has a fault.
  • the power of the smart device is basically reduced at a constant speed, and the power consumption of the smart device is maintained at a relatively stable level. If, if an abnormal drop in the battery voltage is found, the battery itself may be malfunctioning, or a component in the smart device may malfunction and cause abnormal power consumption.
  • step S64 to step S66 based on the current voltage change rate of the battery voltage of the smart device, and the voltage difference between the preset voltage change rate of the battery voltage of the smart device at the normal time, if the smart device battery If the voltage difference of the voltage exceeds a second threshold, for example, 100%, it is determined that the smart device has failed.
  • a second threshold for example, 100%
  • smart locks are also taken as an example for explanation.
  • FIG. 3 when an electrical component in the smart lock circuit board is abnormal, a rapid drop in battery power may occur, and the smart lock itself is still able to maintain normal operation. Although the smart lock can temporarily maintain normal operation, this abnormal situation is likely to cause more serious equipment failure, and the battery power will be quickly consumed.
  • it is impossible to detect and find such a fault and can only be found when the device is exhausted or the fault is aggravated and the device cannot work normally.
  • the foregoing method for determining an average voltage change rate may include:
  • Step S661 obtaining a current voltage change rate of the smart device.
  • Step S663 obtaining an average voltage change rate of the smart device in a normal operating state.
  • Step S665 calculating a new average voltage change rate according to the current voltage change rate and the average voltage change rate.
  • the battery voltage in the smart device can be detected by using the above steps S661 to S665.
  • the average voltage curve and the average voltage change rate can be calculated according to the battery voltage collected when the smart lock is in the normal working state. Diagnose smart locks for problems by using the current rate of change of voltage versus the average rate of change of voltage under normal operating conditions.
  • all smart locks are connected to servers in the Internet, and the server can obtain and store a large number of operational data of the smart locks in normal operation. Using big data processing methods, you can calculate intelligence from these operational data The value of the lock in the normal state.
  • the preset average voltage change rate is obtained by the battery voltage curve of the smart device in normal operation, and the battery voltage curve of the smart device in normal operation is averaged by the battery voltage curve of a large number of trouble-free door locks recorded by the server.
  • the server may pre-collect a certain number of battery voltage data of a smart lock connected to the server through a network, and calculate an average voltage curve from the voltage data.
  • the smart lock uses a new battery when it is newly accessed, and the voltage is the highest, and the battery discharge voltage gradually decreases. When the battery is nearly exhausted, the battery voltage drops to a level where the smart device cannot operate normally.
  • the server obtains a curve of the battery voltage of each device over time by recording the change of the battery voltage of each smart device from the full battery to the exhaustion of the battery, and averaging the voltage curves of all the door locks connected to the server to obtain the battery.
  • the average voltage curve of the voltage as a function of time. It can be considered that the average voltage curve thus obtained can represent the power consumption condition of the smart device during normal operation. Therefore, for the smart lock that needs fault diagnosis, after calculating the current voltage change rate of the current voltage drop, only the average voltage curve is required.
  • the average voltage change rate may be compared. If the current voltage change rate is greater than the average voltage change rate and exceeds a predetermined threshold, it is determined that there is a fault.
  • the battery voltage drop rate is calculated to be 0.05V/day, and the average voltage curve is at a voltage drop rate of 4.67V at a voltage drop rate of 0.01V per day. It is judged to be a failure by 400% of the average voltage curve exceeding a preset threshold of 100%.
  • the original average voltage curve can be updated according to the voltage data of the smart device for fault diagnosis.
  • the recorded voltage curve is added to the data of the average voltage curve, and the new average voltage is updated.
  • the curve so that by collecting more voltage data of the smart device in normal operation, more accurate data will be obtained.
  • the historical voltage of a certain number of smart locks pre-recorded by the server is used.
  • the voltage data of the smart lock is added to the historical voltage database to update the average voltage curve used to determine the fault, which will result in a more accurate average voltage curve.
  • a temperature sensor can also be provided in the smart device. Therefore, the operational data can also include: ambient temperature.
  • the voltage difference between the current voltage change rate and the preset average voltage change rate is compared with the preset second threshold value, and the diagnosis of whether the smart device is faulty may include:
  • Step S667 correcting the second threshold according to the ambient temperature, to obtain a third threshold for determining whether the smart device has a hardware failure.
  • Step S669 when the voltage difference exceeds the third threshold, it is determined that the smart device has a hardware failure.
  • a temperature sensor is set in the standby to monitor the ambient temperature at which the smart device is located.
  • the second threshold for determining whether the smart device has failed is corrected according to the collected ambient temperature, and a third threshold corresponding to the current ambient temperature is generated.
  • the third threshold is used to compare the voltage change rates, thereby improving the diagnostic accuracy of the smart device.
  • the correction process for the second threshold may be: setting the third threshold to be twice the second threshold when the temperature sensor detects that the ambient temperature of the battery is below 0 degrees Celsius; or, by using the battery at different temperatures The power consumption is tested, the third threshold value at different temperatures is obtained, the third threshold at different temperatures is recorded, and the correspondence between the temperature and the third threshold is stored in the memory of the smart device, according to the actual temperature measured by the temperature sensor. A corresponding third threshold is obtained in the memory.
  • the smart lock is also taken as an example for explanation. Since the battery discharge is greatly affected by the ambient temperature, the temperature sensor can be added to the smart lock and the temperature information can be added to the handshake communication information sent by the smart lock. Alternatively, the location rate information of the smart lock can be stored in the server, and the temperature range of the smart lock can be simulated according to the geographic location and time information to correct the rate of change of the voltage. In this way, the server will obtain the ambient temperature value and the voltage value at the same time, and then calculate the battery voltage curve at different temperatures more accurately through a large amount of data, and can also judge whether the smart lock voltage is abnormally dropped at different temperatures according to the ambient temperature information.
  • the method further includes:
  • Step S108 after determining that the smart device has failed, generating alarm information corresponding to the fault.
  • the alarm information corresponding to the fault may be generated. And send the alarm information to the maintenance personnel.
  • the running data further includes: a smart device ID, a password input record, and an operation record.
  • the smart device may be assigned a corresponding smart device ID, and the smart device ID is used as the unique identification information of the smart device. You can use a password to enter records and manipulate records to record user behavior.
  • the embodiment of the invention further provides a smart device fault diagnosis device.
  • the smart device fault diagnosis apparatus according to the embodiment of the present invention may be used to perform the smart device fault diagnosis method provided by the embodiment of the present invention, and the smart device fault diagnosis method according to the embodiment of the present invention may also be adopted by the embodiment of the present invention.
  • a smart device fault diagnosis device is provided to perform.
  • the smart device fault diagnosis apparatus may include: a connection module 22, an acquisition module 24, and a diagnosis module 26.
  • the connection module 22 is configured to establish a communication connection with the smart device, and the obtaining module 24 is configured to pass the communication.
  • the connection data is obtained, and the operation data of the smart device is obtained, wherein the operation data includes at least: a signal strength of the communication connection and/or a battery voltage of the smart device; and the diagnosis module 26 is configured to diagnose whether the smart device is faulty according to the operation data of the smart device. .
  • connection module 22, the acquisition module 24, and the diagnosis module 26 can obtain the running data of the smart device in operation in real time by using the communication connection established with the smart device.
  • the diagnosis of the running status of the smart device is realized by the parameters of the acquired running data and the changes.
  • the obtaining module 24 may include: a sub-receiving module 41 and a sub-transmission module 43.
  • the sub-receiving module 41 is configured to receive the running data sent by the smart device according to the preset first time interval.
  • the sub-transmission module 43 is configured to feed back the acknowledgement signal corresponding to the running data to the smart device.
  • the operating data of the smart device may be acquired by using the sub-receiving module 41 and the sub-sending module 43 in the form of communication of the handshake communication.
  • the smart device sends the running data to the server according to the preset first time interval. After receiving the running data sent by the smart terminal, the server returns an acknowledgement signal for receiving the running data to the smart device.
  • the server returns an acknowledgement signal for receiving the running data to the smart device.
  • the obtaining module 24 may further include: a sub-acquisition module 45, a first sub-determination module 47, and a second sub-determination module 49.
  • the sub-acquisition module 45 is configured to acquire the receiving time of the running data sent by the smart device, and the first sub-determining module 47 is configured to determine the current system time and the receiving time according to the receiving time and the current system time.
  • the second sub-determination module 49 is configured to compare the second time interval with a preset time threshold to determine whether the smart device has failed.
  • the foregoing sub-acquisition module 45, the first sub-determination module 47, and the second sub-determination module 49 acquire the receiving time when receiving the running data sent by the smart device, and determine the current system according to the receiving time and the current system time.
  • the second time interval between the time and the last received run data.
  • the second time interval is compared with a preset time threshold to determine whether the smart device has failed by using the comparison result of the second time interval and the time threshold.
  • the threshold can be determined according to the actual network environment. Of course, it can also be determined according to the first time interval.
  • the following steps may be performed:
  • step A according to the received signal strength, a signal strength record corresponding to the smart device is generated in chronological order.
  • step B the signal strength average of the signal strength is determined according to the signal strength record.
  • Step C When the signal strength difference between the received signal strength and the signal strength average is greater than a preset first threshold, determining that the smart device has a communication failure.
  • the smart lock is taken as an example for description.
  • the smart lock contains wireless signal strength information in each handshake communication message.
  • the server can use the received wireless signal strength information to calculate the average signal strength for a certain period of time. For example, the average signal strength within 1-24 hours before the current time can be calculated to obtain the signal strength mean.
  • the current signal strength is compared with the signal strength average. If the current signal strength is lower than the signal strength mean value exceeds a preset first threshold, the smart lock can be diagnosed to have a communication failure.
  • the following steps may be performed:
  • step a a battery voltage record corresponding to the smart device is generated in chronological order according to the received battery voltage.
  • Step b calculating a current voltage change rate of the current battery voltage of the smart device according to the battery voltage record.
  • step c the voltage difference between the current voltage change rate and the preset average voltage change rate is compared with a preset second threshold to diagnose whether the smart device is faulty.
  • the power of the smart device is basically reduced at a constant speed, and the power consumption of the smart device is maintained at a relatively stable level. If, if an abnormal drop in the battery voltage is found, the battery itself may be malfunctioning, or a component in the smart device may malfunction and cause abnormal power consumption.
  • the method for determining the average voltage change rate may include:
  • step c1 the current voltage change rate of the smart device is obtained.
  • step c2 the average voltage change rate of the smart device under normal operating conditions is obtained.
  • step c3 the new average voltage change rate is calculated according to the current voltage change rate and the average voltage change rate.
  • a temperature sensor can also be provided in the smart device. Therefore, the number of runs It can also include: ambient temperature.
  • the diagnosis module 26 may further include:
  • step c4 the second threshold is corrected according to the ambient temperature, and a third threshold for determining whether the smart device has a hardware failure is obtained.
  • step c5 when the voltage difference exceeds the third threshold, it is determined that the smart device has a hardware failure.
  • a temperature sensor can be set in the smart device to monitor the ambient temperature at which the smart device is located.
  • the diagnosis module 26 is configured to perform a correction process on the second threshold for determining whether the smart device has failed according to the collected ambient temperature, and generate a third threshold corresponding to the current ambient temperature.
  • the third threshold is used to compare the voltage change rates, thereby improving the diagnostic accuracy of the smart device.
  • the correction process for the second threshold may be: setting the third threshold to be twice the second threshold when the temperature sensor detects that the ambient temperature of the battery is below 0 degrees Celsius; or, by using the battery at different temperatures The power consumption is tested, the third threshold value at different temperatures is obtained, the third threshold at different temperatures is recorded, and the correspondence between the temperature and the third threshold is stored in the memory of the smart device, according to the actual temperature measured by the temperature sensor. A corresponding third threshold is obtained in the memory.
  • the foregoing apparatus may further include: a prompting module 28.
  • the prompting module 28 is configured to generate alarm information corresponding to the fault after determining that the smart device is faulty.
  • the alarm information corresponding to the fault may be generated. And send the alarm information to the maintenance personnel.
  • the running data further includes: a smart device ID, a password input record, and an operation record.
  • the smart device may be assigned a corresponding smart device ID, and the smart device ID is used as the unique identification information of the smart device. You can use a password to enter records and manipulate records to record user behavior.
  • the disclosed technical contents may be implemented in other manners.
  • the device embodiments described above are only schematic.
  • the division of the unit may be a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, unit or module, and may be electrical or otherwise.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium.
  • the technical solution of the present invention which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium.
  • a number of instructions are included to cause a computer device (which may be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes: a U disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk, and the like. .

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Abstract

一种设备故障诊断方法、装置及***。其中，该方法包括：建立与智能设备（10）的通讯连接（S102）；通过通讯连接，获取智能设备（10）的运行数据（S104），其中，运行数据至少包括：通讯连接的信号强度和/或智能设备（10）的电池电压；根据智能设备（10）的运行数据，诊断智能设备（10）是否发生故障（S106）。该技术方案解决了由于无法对智能家居设备的故障进行检测、报警，导致的用户使用体验差的技术问题。

Description

设备故障诊断方法、装置及*** 技术领域
本发明涉及物联网领域，具体而言，涉及一种设备故障诊断方法、装置及***。
背景技术
现有的物联网设备和智能家居设备一般不具备故障诊断的功能，对于某些关键设备，例如：智能门锁、门禁***等设备，如果出现故障会严重影响用户的使用体验，严重时还会影响用户的人身财产安全。因此，如何快速的检测故障的发生以及如何能够预测发生潜在故障的可能，对于设备的使用者来说有很大的意义。
在现有技术中，部分门锁***安装有传感器或者微动开关，来对门锁的特定部件进行监控，从而起到故障检测的作用。但是，上述方法能检测到的故障种类单一，报警也不及时。因此，现有的智能家居设备无法提供可靠的故障检测功能，更无法针对设备目前运行状况进行故障的诊断和预测。一少部分智能家居设备虽然具有故障检测功能，但是能够检测的设备故障单一，无法实时向用户提供故障警报。
针对现有技术中的由于无法对智能家居设备的故障进行检测、报警，导致的用户使用体验差的问题，目前尚未提出有效的解决方案。
发明内容
本发明实施例提供了一种设备故障诊断方法、装置及***，以至少解决由于无法对智能家居设备的故障进行检测、报警，导致的用户使用体验差的技术问题。
根据本发明实施例的一个方面，提供了一种智能设备故障诊断方法，包括：建立与智能设备的通讯连接；通过通讯连接，获取智能设备的运行数据，其中，运行数据至少包括：通讯连接的信号强度和/或智能设备的电池电压；根据智能设备的运行数据，诊断智能设备是否发生故障。
进一步地，通过通讯连接，获取智能设备的运行数据，包括：接收智能设备按照预先设置的第一时间间隔发送的运行数据；向智能设备反馈与运行数据对应的确收信号。
进一步地，通过通讯连接，获取智能设备的运行数据，还包括：获取接收到智能 设备发送的运行数据的接收时间；根据接收时间和当前***时间，确定当前***时间与接收时间之间的第二时间间隔；将第二时间间隔与预先设置的时间阈值进行比对，确定智能设备是否发生故障。
进一步地，当运行数据为信号强度时，根据智能设备的运行数据，诊断智能设备是否发生故障，包括：根据接收到信号强度，按照时间顺序生成与智能设备对应的信号强度记录；根据信号强度记录，确定信号强度的信号强度均值；当接收到的信号强度与信号强度均值的信号强度差值大于预先设置的第一阈值时，确定智能设备发生通讯故障。
进一步地，当运行数据为电池电压时，根据智能设备的运行数据，诊断智能设备是否发生故障，包括：根据接收到的电池电压，按照时间顺序生成与智能设备对应的电池电压记录；根据电池电压记录，计算智能设备当前电池电压的当前电压变化率；将当前电压变化率与预先设置的平均电压变化率的电压差值与预先设置第二阈值进行比对，诊断智能设备是否发生故障。
进一步地，上述平均电压变化率的确定方法包括：获取智能设备的当前电压变化率；获取智能设备在正常运行状态下的平均电压变化率；根据当前电压变化率与平均电压变化率，计算新平均电压变化率。
进一步地，运行数据还包括：环境温度，其中，将当前电压变化率与预先设置的平均电压变化率的电压差值与预先设置第二阈值进行比对，诊断智能设备是否发生故障，包括：根据环境温度对第二阈值进行修正，得到用于确定智能设备是否发生硬件故障的第三阈值；当电压差值超过第三阈值时，确定智能设备发生硬件故障。
进一步地，在根据智能设备的运行数据，诊断智能设备是否发生故障之后，方法还包括：当确定智能设备发生故障后，生成与故障对应的报警信息。
进一步地，运行数据还包括：智能设备ID、密码输入记录、操作记录。
根据本发明实施例的另一方面，还提供了一种智能设备故障诊断装置，包括：连接模块，用于建立与智能设备的通讯连接；获取模块，用于通过通讯连接，获取智能设备的运行数据，其中，运行数据至少包括：通讯连接的信号强度和/或智能设备的电池电压；诊断模块，用于根据智能设备的运行数据，诊断智能设备是否发生故障。
进一步地，获取模块包括：子接收模块，用于接收智能设备按照预先设置的第一时间间隔发送的运行数据；子发送模块，用于向智能设备反馈与运行数据对应的确收信号。
进一步地，获取模块还包括：子获取模块，用于获取接收到智能设备发送的运行数据的接收时间；第一子确定模块，用于根据接收时间和当前***时间，确定当前***时间与接收时间之间的第二时间间隔；第二子确定模块，用于将第二时间间隔与预先设置的时间阈值进行比对，确定智能设备是否发生故障。
进一步地，装置还包括：提示模块，用于当确定智能设备发生故障后，生成与故障对应的报警信息。
根据本发明实施例的另一方面，还提供了一种智能设备故障诊断***，包括：智能设备，用于按照预先设置的时间间隔发送运行数据；无线网关，与智能设备无线连接，用于建立服务器与智能设备之间的通讯连接；服务器，与无线网关连接，用于通过无线网关获取智能设备的运行数据，并且，根据智能设备的运行数据，诊断智能设备是否发生故障。
在本发明实施例中，采用建立与智能设备的通讯连接；通过通讯连接，获取智能设备的运行数据，其中，运行数据至少包括：通讯连接的信号强度和/或智能设备的电池电压；根据智能设备的运行数据，诊断智能设备是否发生故障的方式，达到了对智能设备的工作状态进行监控的目的，从而实现了利用监控的到的运行数据，对智能设备的故障进行预测的技术效果，进而解决了由于无法对智能家居设备的故障进行检测、报警，导致的用户使用体验差的技术问题。
附图说明
此处所说明的附图用来提供对本发明的进一步理解，构成本申请的一部分，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。在附图中：
图1是根据本发明实施例的智能设备故障诊断***的示意图；
图2是根据本发明实施例的智能设备故障诊断方法的流程图；
图3是根据本发明实施例的智能设备故障诊断方法在实际应用中的流程图；
图4是根据本发明实施例的智能设备故障诊断装置的示意图；以及
图5是根据本发明实施例的一种可选的智能设备故障诊断的装置示意图。
具体实施方式
为了使本技术领域的人员更好地理解本发明方案，下面将结合本发明实施例中的 附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分的实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都应当属于本发明保护的范围。
需要说明的是，本发明的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本发明的实施例能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、***、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
根据本发明实施例，提供了一种智能设备故障诊断***的实施例，图1是根据本发明实施例的智能设备故障诊断***的示意图，如图1所示，该智能设备故障诊断***包括：智能设备10、无线网关20和服务器30。
其中，智能设备10，用于按照预先设置的时间间隔发送运行数据；无线网关20，与智能设备10无线连接，用于建立服务器30与智能设备10之间的通讯连接；服务器30，与无线网关20连接，用于通过无线网关20获取智能设备10的运行数据，并且，根据智能设备10的运行数据，诊断智能设备10是否发生故障。
通过上述智能设备10、无线网关20和服务器30，利用与智能设备建立的通讯连接，可以实时获取智能设备在运行中的运行数据。通过对获取到的运行数据的各项参数以及变化情况，实现对智能设备的运行状况进行诊断。通过上述方法，达到了对智能设备的工作状态进行监控的目的，从而实现了利用监控的到的运行数据，对智能设备的故障进行预测的技术效果。进而解决了由于无法对智能家居设备的故障进行检测、报警，导致的用户使用体验差的技术问题。
在智能设备中具有无线通讯模块，智能设备可以通过该无线通讯模块与无线网关进行通讯，并通过无线网关连接到互联网中的服务器；该无线通讯模块能够记录智能设备与无线网关之间的无线信号强度。智能设备还能够记录所用电池的实时电压值。智能设备通过以固定的时间间隔与无线网关进行握手通讯，在每次握手通讯时，智能设备向服务器发送无线信号强度和电压值，互联网服务器记录无线信号强度和电压值，并通过计算诊断智能设备是否故障。
根据本发明实施例，提供了一种智能设备故障诊断方法实施例，需要说明的是， 在附图的流程图示出的步骤可以在诸如一组计算机可执行指令的计算机***中执行，并且，虽然在流程图中示出了逻辑顺序，但是在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤。
图2是根据本发明实施例的智能设备故障诊断方法的流程图，如图2所示，该方法包括如下步骤：
步骤S102，建立与智能设备的通讯连接。
步骤S104，通过通讯连接，获取智能设备的运行数据，其中，运行数据至少包括：通讯连接的信号强度和智能设备的电池电压。
步骤S106，根据智能设备的运行数据，诊断智能设备是否发生故障。
具体的，通过步骤S102至步骤S106，利用与智能设备建立的通讯连接，可以实时获取智能设备在运行中的运行数据。通过对获取到的运行数据的各项参数以及变化情况，实现对智能设备的运行状况进行诊断。通过上述方法，达到了对智能设备的工作状态进行监控的目的，从而实现了利用监控的到的运行数据，对智能设备的故障进行预测的技术效果。进而解决了由于无法对智能家居设备的故障进行检测、报警，导致的用户使用体验差的技术问题。
作为一种可选的实施方式，在建立与智能设备的通讯连接的步骤中所使用的连接方式，可以为有线连接或者无线连接。其中，采用有线连接具有传输稳定、结构简单等优点，但是因其布线复杂，前期成本较高。采用无线连接的方式建立通讯连接可以很好的解决布线问题，可以利用WIFI、蓝牙、移动通讯网络等方式实现。具体的使用的连接方式，可以根据实际需要而确定，此处不做具体限制。
作为一种可选的实施方式，步骤S104通过通讯连接，获取智能设备的运行数据的步骤，可以包括：
步骤S41，接收智能设备按照预先设置的第一时间间隔发送的运行数据。
步骤S43，向智能设备反馈与运行数据对应的确收信号。
具体的，在获取智能设备的运行数据时，可以通过上述步骤S41至步骤S43，以握手通讯的通讯形式获取智能设备的运行数据。其中，智能设备按照预先设置的第一时间间隔向服务器发送运行数据，服务器在接收到智能终端发送的运行数据之后，向智能设备返回接收到该运行数据的确收信号。通过上述方式不但可以实时获取到设备的运行数据，还可以避免因持续连接导致的通讯模块发热量大、功耗高的问题。
作为一种可选的实施方式，以智能锁为例进行说明。智能锁可以通过无线通讯的方式与无线网关连接，并进一步通过无线网关与互联网中的服务器连接。其中，智能锁在正常工作时，每间隔预设时间与互联网服务器进行握手通讯(发送一段通讯数据后接收一段服务器反馈数据)，这样服务器能够及时获取智能锁的在线状态和运行状态。其中，智能锁发送的握手通讯的信息中可以包括：智能锁的ID、智能锁的无线信号强度、智能锁的电池电压值、智能锁的密码输入情况、智能锁的刷卡情况、智能锁的把手动作记录等，服务器可以记录智能锁发送的所有握手通讯数据，并根据无线信号强度和电池电压值计算生成无线信号强度曲线和电池电压曲线。
作为一种可选的实施方式，在获取智能设备的运行数据时，也可以采用服务器按照预先设定的第一时间频率向智能设备端发送数据请求信号，智能设备在接收到数据请求后返回当前智能设备的运行数据的方式实现。
作为一种可选的实施方式，在步骤S104通过通讯连接，获取智能设备的运行数据的步骤中，上述步骤还可以包括：
步骤S45，获取接收到智能设备发送的运行数据的接收时间。
步骤S47，根据接收时间和当前***时间，确定当前***时间与接收时间之间的第二时间间隔。
步骤S49，将第二时间间隔与预先设置的时间阈值进行比对，确定智能设备是否发生故障。
具体的，通过步骤S45至步骤S49，获取在接收智能设备发送的运行数据时的接收时间，并根据接收时间和当前***时间，确定当前***时间与上一次接收到运行数据之间的第二时间间隔。将第二时间间隔与预先设置的时间阈值进行比对，从而利用第二时间间隔与时间阈值的比对结果，确定智能设备是否发生故障。其中，阈值可以根据实际网络环境确定。当然，也可以根据第一时间间隔确定。
作为一种可选的实施方式，还以智能锁为例进行说明。如果服务器连续一定时间无法接收到来自智能锁发送的握手通讯数据，则可以直接判定通讯故障。例如，可以设定智能锁以每隔20-40秒发起一次握手通讯，如果服务器在预定时间内没有收到智能锁发送的握手通讯数据，服务器则可以诊断智能锁发生通讯故障，其中，时间可以是通讯间隔即第一时间间隔的整数倍，例如设定时间为5个通讯间隔。具体根据实际情况进行设定，此处不做具体限制。
作为一种可选的实施方式，在服务器能够正常接收握手通讯数据的情况下，服务器可以通过计算智能锁无线信号的平均强度，并将实时获取到的信号强度与平均信号 强度进行对比，如果当前信号强度低于平均信号强度的幅度超过预先设定的阈值，则判断为通讯故障；服务器根据电池电压曲线计算电压下降速度，当电池电压下降速度大于预先设定的阈值时，判断智能锁故障。
在现有技术中，无法检测出该类型的故障，也无法根据信号的异常波动预测可能出现的故障。上述方法可以通过监控智能设备的工作状态，及时发现异常情况，并可以通知客户及时进行检修处理。
作为一种可选的实施方式，当运行数据为信号强度时，在步骤S106根据智能设备的运行数据，诊断智能设备是否发生故障中，可以包括：
步骤S61，根据接收到信号强度，按照时间顺序生成与智能设备对应的信号强度记录。
步骤S62，根据信号强度记录，确定信号强度的信号强度均值。
步骤S63，当接收到的信号强度与信号强度均值的信号强度差值大于预先设置的第一阈值时，确定智能设备发生通讯故障。
具体的，还以智能锁为例进行说明。智能锁在每次握手通讯信息中均包含无线信号强度信息。当智能锁通讯正常且正常运行时，服务器可以利用接收到的无线信号强度信息，计算在之前一定时间内的平均信号强度。例如，可以计算距离当前时间之前1-24小时内的平均信号强度，得到信号强度均值。并将当前信号强度与信号强度均值进行对比，如果当前信号强度低于信号强度均值的幅度超过预先设定的第一阈值时，则可以诊断智能锁发生通讯故障。
其中，第一阈值也可以是比值，当当前的信号强度低于信号强均值的50％或70％时，则可以诊断智能锁发生通讯故障。而当前的信号强度，可以是最近一次握手通讯信息中包含的信号强度，也可以是最近5-10次握手通讯信息中包含的信号强度的平均值，优选使用最近接收到的预定次数信号强度的平均值，这样避免由于偶然一次信号强度降低，而导致的误报故障的发生概率。
对于智能锁来说，在正常的工作状态下，由于智能锁和网关所处的位置相对固定，因此，他们之间通过无线连接的信号强度应该可以保持相对稳定。如果信号强度在某一时刻出现大幅下降，虽然这时智能锁仍然能够维持正常通讯和正常工作，但是，这种信号低于正常值的状态很可能是由于智能锁的通讯电路、天线等部件出现异常导致的。随时可能出现更严重的通讯故障。
作为一种可选的实施方式，当运行数据为电池电压时，在步骤S106根据智能设备 的运行数据，诊断智能设备是否发生故障中，可以包括：
步骤S64，根据接收到的电池电压，按照时间顺序生成与智能设备对应的电池电压记录。
步骤S65，根据电池电压记录，计算智能设备当前电池电压的当前电压变化率。
步骤S66，将当前电压变化率与预先设置的平均电压变化率的电压差值与预先设置第二阈值进行比对，诊断智能设备是否发生故障。
具体的，在正常的工作状态下，智能设备的电量基本为匀速降低，智能设备的功耗维持在一个相对稳定的水平。如果，一旦发现电池电压出现异常下降时，则说明电池本身可能出现故障，或者智能设备中某个部件发生故障而导致异常耗电。
通过步骤S64至步骤S66，根据智能设备的电池电压的当前电压变化率，与预先设定的智能设备在正常时电池电压的平均电压变化率之间的电压差值来进行判断，如果智能设备电池电压的电压差值超过第二阈值，例如100％，则判断该智能设备发生故障。
在实际应用当中，还以智能锁为例进行说明。如图3所示，当智能锁的电路板中的某个电气元件发生异常时，可能出现电池电量快速下降的情况，此时的智能锁本身往往仍然能够维持正常运行。虽然智能锁可以暂时维持正常工作，但是这种异常情况很可能造成更严重的设备故障，并且电池电量也会因此而快速消耗完。在现有的技术中并无法检测并发现这种故障，只能等到设备电量耗尽或者故障加重造成设备无法正常工作时才能发现。
作为一种可选的实施方式，上述平均电压变化率的确定方法可以包括：
步骤S661，获取智能设备的当前电压变化率。
步骤S663，获取智能设备在正常运行状态下的平均电压变化率。
步骤S665，根据当前电压变化率与平均电压变化率，计算新平均电压变化率。
具体的，利用上述步骤S661至步骤S665，可以对于智能设备中的电池电压进行检测。当出现电池电压异常下降时，可以根据智能锁处于正常工作状态时采集到的电池电压计算得到平均电压曲线以及平均电压变化率。通过使用当前的电压变化率与正常工作状态下的平均电压变化率进行对比，来诊断智能锁是否出现问题。在使用中，所有智能锁都与互联网中的服务器连接，服务器可以获得并储存大量智能锁在正常运行状态中的运行数据。利用大数据处理的方法，可以从这些运行数据中计算得到智能 锁在正常状态下的数值。
在实际应用当中，预设的平均电压变化率通过处于正常工作的智能设备的电池电压曲线获得，处于正常工作的智能设备的电池电压曲线通过服务器记录的大量无故障门锁的电池电压曲线平均得到。举例来说，服务器可以预先采集一定数目通过网络与服务器连接的智能锁的电池电压数据，通过这些电压数据计算出平均电压曲线。在处于正常工作情况下，智能锁在新接入时使用新电池，电压最高，而随着电池放电电压逐渐降低。当电量接近耗尽后电池电压降低到无法维持智能设备正常工作的水平。服务器通过记录每个智能设备的电池电压从电池满电到电量耗尽的变化情况，得到每个设备电池电压随时间变化的曲线，通过对连接服务器的所有门锁的电压曲线进行平均，得到电池电压随时间变化的平均电压曲线。可以认为这样得到的平均电压曲线能够代表智能设备正常工作时的耗电情况，因此对于需要故障诊断的智能锁，在计算得到当前电压下降的当前电压变化率后，只需要与平均电压曲线对应的平均电压变化率的进行比对即可，如果当前电压变化率大于平均电压变化率的值超过预先设定的阈值时，即可判定存在故障。例如，通过监控记录到智能锁的电池电压为4.67V，计算电池电压的下降速度为0.05V/天，而平均电压曲线在电压为4.67V处的电压下降速度为0.01V每天，两者的差为平均电压曲线的400％，超过预先设定的100％的阈值，判定为故障。
另外，可以后续根据故障诊断的智能设备的电压数据对原始的平均电压曲线进行更新，对于判定正常工作的设备，将记录到的电压曲线加入到平均电压曲线的数据中，更新得到新的平均电压曲线，这样通过收集更多的处于正常工作的智能备的电压数据，将得到更准确的数据。例如，在初始进行故障诊断时，使用的是服务器预先记录的一定数目智能锁的历史电压，当使用历史数据对当前在线的所有智能锁进行故障诊断时，每次诊断完成后，将判断正常的智能锁的电压数据加入历史电压数据库，从而对用于判断故障的平均电压曲线进行更新，这样将得到更准确的平均电压曲线。
作为一种可选的实施方式，还可以在智能设备中设置温度传感器。因此，运行数据还可以包括：环境温度。其中，在步骤S66将当前电压变化率与预先设置的平均电压变化率的电压差值与预先设置第二阈值进行比对，诊断智能设备是否发生故障中，可以包括：
步骤S667，根据环境温度对第二阈值进行修正，得到用于确定智能设备是否发生硬件故障的第三阈值。
步骤S669，当电压差值超过第三阈值时，确定智能设备发生硬件故障。
具体的，由于电池的放电性能收到环境温度的影响比较大，因此，可以在智能设 备中设置温度传感器来监控智能设备所处的环境温度。利用步骤S667至步骤S669，根据采集到的环境温度对用于判断智能设备是否发生故障的第二阈值进行修正处理，生成与当前环境温度对应的第三阈值。利用第三阈值对电压变化率进行比对，从而提高对与智能设备的诊断精度。例如，对第二阈值的修正处理可以是：当温度传感器探测到电池所处的环境温度低于0摄氏度时，设置第三阈值为第二阈值的两倍；或者，通过在不同温度下对电池耗电情况进行试验，获得不同温度下第三阈值的值，记录不同温度下的第三阈值并将温度和第三阈值的对应关系存储在智能设备的存储器中，根据温度传感器测量的实际温度在存储器中获取对应的第三阈值。
还以智能锁为例进行说明。由于电池放电受环境温度影响很大，因此，可以在智能锁中增加温度传感器，并将温度信息添加到智能锁发送的握手通讯信息中。或者，还可以通过在服务器中存储智能锁安装的地理位置信息，并根据地理位置和时间信息模拟计算智能锁所处环境温度范围，对电压的变化率进行修正。这样，服务器将同时获得环境温度值和电压值，进而通过大量数据更精确的计算出不同温度下电池电压曲线，也可以根据环境温度信息判断不同温度下智能锁电压是否异常下降。
作为一种可选的实施方式，在步骤S106根据智能设备的运行数据，诊断智能设备是否发生故障之后，方法还包括：
步骤S108，当确定智能设备发生故障后，生成与故障对应的报警信息。
具体的，在诊断得到智能设备的故障之后，可以生成与故障对应的报警信息。并将报警信息发送给维护人员。
作为一种可选的实施方式，所述运行数据还包括：智能设备ID、密码输入记录、操作记录。
具体的，可以为智能设备分配相应的智能设备ID，并将智能设备ID作为智能设备的唯一标识信息。可以利用密码输入记录和操作记录，实现对用户行为进行记录。
本发明实施例还提供了一种智能设备故障诊断装置。需要说明的是，本发明实施例的智能设备故障诊断装置可以用于执行本发明实施例所提供的智能设备故障诊断方法，本发明实施例的智能设备故障诊断方法也可以通过本发明实施例所提供的智能设备故障诊断装置来执行。
图4是根据本发明实施例的智能设备故障诊断装置的示意图。如图4所示，该智能设备故障诊断装置可以包括：连接模块22、获取模块24和诊断模块26。
其中，连接模块22，用于建立与智能设备的通讯连接；获取模块24，用于通过通 讯连接，获取智能设备的运行数据，其中，运行数据至少包括：通讯连接的信号强度和/或智能设备的电池电压；诊断模块26，用于根据智能设备的运行数据，诊断智能设备是否发生故障。
具体的，通过连接模块22、获取模块24和诊断模块26，利用与智能设备建立的通讯连接，可以实时获取智能设备在运行中的运行数据。通过对获取到的运行数据的各项参数以及变化情况，实现对智能设备的运行状况进行诊断。通过上述方法，达到了对智能设备的工作状态进行监控的目的，从而实现了利用监控的到的运行数据，对智能设备的故障进行预测的技术效果。进而解决了由于无法对智能家居设备的故障进行检测、报警，导致的用户使用体验差的技术问题。
作为一种可选的实施方式，获取模块24可以包括：子接收模块41和子发送模块43。
其中，子接收模块41，用于接收智能设备按照预先设置的第一时间间隔发送的运行数据；子发送模块43，用于向智能设备反馈与运行数据对应的确收信号。
具体的，在获取智能设备的运行数据时，可以通过上述子接收模块41和子发送模块43，以握手通讯的通讯形式获取智能设备的运行数据。其中，智能设备按照预先设置的第一时间间隔向服务器发送运行数据，服务器在接收到智能终端发送的运行数据之后，向智能设备返回接收到该运行数据的确收信号。通过上述方式不但可以实时获取到设备的运行数据，还可以避免因持续连接导致的通讯模块发热量大、功耗高的问题。
作为一种可选的实施方式，获取模块24还可以包括：子获取模块45、第一子确定模块47和第二子确定模块49。
其中，子获取模块45，用于获取接收到智能设备发送的运行数据的接收时间；第一子确定模块47，用于根据接收时间和当前***时间，确定当前***时间与接收时间之间的第二时间间隔；第二子确定模块49，用于将第二时间间隔与预先设置的时间阈值进行比对，确定智能设备是否发生故障。
具体的，通过上述子获取模块45、第一子确定模块47和第二子确定模块49，获取在接收智能设备发送的运行数据时的接收时间，并根据接收时间和当前***时间，确定当前***时间与上一次接收到运行数据之间的第二时间间隔。将第二时间间隔与预先设置的时间阈值进行比对，从而利用第二时间间隔与时间阈值的比对结果，确定智能设备是否发生故障。其中，阈值可以根据实际网络环境确定。当然，也可以根据第一时间间隔确定。
作为一种可选的实施方式，当运行数据为信号强度时，在上述诊断模块26中，可以执行如下步骤：
步骤A，根据接收到信号强度，按照时间顺序生成与智能设备对应的信号强度记录。
步骤B，根据信号强度记录，确定信号强度的信号强度均值。
步骤C，当接收到的信号强度与信号强度均值的信号强度差值大于预先设置的第一阈值时，确定智能设备发生通讯故障。
具体的，还以智能锁为例进行说明。智能锁在每次握手通讯信息中均包含无线信号强度信息。当智能锁通讯正常且正常运行时，服务器可以利用接收到的无线信号强度信息，计算在之前一定时间内的平均信号强度。例如，可以计算距离当前时间之前1-24小时内的平均信号强度，得到信号强度均值。并将当前信号强度与信号强度均值进行对比，如果当前信号强度低于信号强度均值的幅度超过预先设定的第一阈值时，则可以诊断智能锁发生通讯故障。
作为一种可选的实施方式，当运行数据为电池电压时，在上述诊断模块26中，可以执行如下步骤：
步骤a，根据接收到的电池电压，按照时间顺序生成与智能设备对应的电池电压记录。
步骤b，根据电池电压记录，计算智能设备当前电池电压的当前电压变化率。
步骤c，将当前电压变化率与预先设置的平均电压变化率的电压差值与预先设置第二阈值进行比对，诊断智能设备是否发生故障。
具体的，在正常的工作状态下，智能设备的电量基本为匀速降低，智能设备的功耗维持在一个相对稳定的水平。如果，一旦发现电池电压出现异常下降时，则说明电池本身可能出现故障，或者智能设备中某个部件发生故障而导致异常耗电。
其中，上述平均电压变化率的确定方法可以包括：
步骤c1，获取智能设备的当前电压变化率。
步骤c2，获取智能设备在正常运行状态下的平均电压变化率。
步骤c3，根据当前电压变化率与平均电压变化率，计算新平均电压变化率。
作为一种可选的实施方式，还可以在智能设备中设置温度传感器。因此，运行数 据还可以包括：环境温度。其中，在上述诊断模块26中，还可以包括：
步骤c4，根据环境温度对第二阈值进行修正，得到用于确定智能设备是否发生硬件故障的第三阈值。
步骤c5，当电压差值超过第三阈值时，确定智能设备发生硬件故障。
具体的，由于电池的放电性能收到环境温度的影响比较大，因此，可以在智能设备中设置温度传感器来监控智能设备所处的环境温度。利用上述诊断模块26，根据采集到的环境温度对用于判断智能设备是否发生故障的第二阈值进行修正处理，生成与当前环境温度对应的第三阈值。利用第三阈值对电压变化率进行比对，从而提高对与智能设备的诊断精度。例如，对第二阈值的修正处理可以是：当温度传感器探测到电池所处的环境温度低于0摄氏度时，设置第三阈值为第二阈值的两倍；或者，通过在不同温度下对电池耗电情况进行试验，获得不同温度下第三阈值的值，记录不同温度下的第三阈值并将温度和第三阈值的对应关系存储在智能设备的存储器中，根据温度传感器测量的实际温度在存储器中获取对应的第三阈值。
作为一种可选的实施方式，如图5所示，上述装置还可以包括：提示模块28。其中，提示模块28，用于当确定智能设备发生故障后，生成与故障对应的报警信息。
具体的，在诊断得到智能设备的故障之后，可以生成与故障对应的报警信息。并将报警信息发送给维护人员。
作为一种可选的实施方式，所述运行数据还包括：智能设备ID、密码输入记录、操作记录。
具体的，可以为智能设备分配相应的智能设备ID，并将智能设备ID作为智能设备的唯一标识信息。可以利用密码输入记录和操作记录，实现对用户行为进行记录。
上述本发明实施例序号仅仅为了描述，不代表实施例的优劣。
在本发明的上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
在本申请所提供的几个实施例中，应该理解到，所揭露的技术内容，可通过其它的方式实现。其中，以上所描述的装置实施例仅仅是示意性的，例如所述单元的划分，可以为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个***，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，单元或模块的间接耦合或通信连接，可以是电性或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可为个人计算机、服务器或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、移动硬盘、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。

Claims (14)

  1. 一种智能设备故障诊断方法，其中，包括：
    建立与智能设备的通讯连接；
    通过所述通讯连接，获取所述智能设备的运行数据，其中，所述运行数据至少包括：所述通讯连接的信号强度和/或所述智能设备的电池电压；
    根据所述智能设备的所述运行数据，诊断所述智能设备是否发生故障。
  2. 根据权利要求1所述的方法，其中，通过所述通讯连接，获取所述智能设备的运行数据，包括：
    接收所述智能设备按照预先设置的第一时间间隔发送的所述运行数据；
    向所述智能设备反馈与所述运行数据对应的确收信号。
  3. 根据权利要求2所述的方法，其中，通过所述通讯连接，获取所述智能设备的运行数据，还包括：
    获取接收到所述智能设备发送的所述运行数据的接收时间；
    根据所述接收时间和当前***时间，确定所述当前***时间与所述接收时间之间的第二时间间隔；
    将所述第二时间间隔与预先设置的时间阈值进行比对，确定所述智能设备是否发生故障。
  4. 根据权利要求2所述的方法，其中，当所述运行数据为所述信号强度时，根据所述智能设备的所述运行数据，诊断所述智能设备是否发生故障，包括：
    根据接收到所述信号强度，按照时间顺序生成与所述智能设备对应的信号强度记录；
    根据所述信号强度记录，确定所述信号强度的信号强度均值；
    当接收到的所述信号强度与所述信号强度均值的信号强度差值大于预先设置的第一阈值时，确定所述智能设备发生通讯故障。
  5. 根据权利要求2所述的方法，其中，当所述运行数据为所述电池电压时，根据所述智能设备的所述运行数据，诊断所述智能设备是否发生故障，包括：
    根据接收到的所述电池电压，按照时间顺序生成与所述智能设备对应的电池电压记录；
    根据所述电池电压记录，计算所述智能设备当前电池电压的当前电压变化率；
    将所述当前电压变化率与预先设置的平均电压变化率的电压差值与预先设置第二阈值进行比对，诊断所述智能设备是否发生故障。
  6. 根据权利要求5所述的方法，其中，所述平均电压变化率的确定方法包括如下步骤：
    获取所述智能设备的所述当前电压变化率；
    获取所述智能设备在正常运行状态下的所述平均电压变化率；
    根据所述当前电压变化率与所述平均电压变化率，计算新平均电压变化率。
  7. 根据权利要求5所述的方法，其中，所述运行数据还包括：环境温度，其中，将所述当前电压变化率与预先设置的平均电压变化率的电压差值与预先设置第二阈值进行比对，诊断所述智能设备是否发生故障，包括：
    根据所述环境温度对所述第二阈值进行修正，得到用于确定所述智能设备是否发生硬件故障的第三阈值；
    当所述电压差值超过所述第三阈值时，确定所述智能设备发生硬件故障。
  8. 根据权利要求1所述的方法，其中，在根据所述智能设备的所述运行数据，诊断所述智能设备是否发生故障之后，所述方法还包括：
    在确定所述智能设备发生故障后，生成与所述故障对应的报警信息。
  9. 根据权利要求1至8中任意一项所述的方法，其中，所述运行数据还包括：智能设备ID、密码输入记录、操作记录。
  10. 一种智能设备故障诊断装置，其中，包括：
    连接模块，用于建立与智能设备的通讯连接；
    获取模块，用于通过所述通讯连接，获取所述智能设备的运行数据，其中，所述运行数据至少包括：所述通讯连接的信号强度和/或所述智能设备的电池电压；
    诊断模块，用于根据所述智能设备的所述运行数据，诊断所述智能设备是否发生故障。
  11. 根据权利要求10所述的装置，其中，所述获取模块包括：
    子接收模块，用于接收所述智能设备按照预先设置的第一时间间隔发送的所述运行数据；
    子发送模块，用于向所述智能设备反馈与所述运行数据对应的确收信号。
  12. 根据权利要求11所述的装置，其中，所述获取模块还包括：
    子获取模块，用于获取接收到所述智能设备发送的所述运行数据的接收时间；
    第一子确定模块，用于根据所述接收时间和当前***时间，确定所述当前***时间与所述接收时间之间的第二时间间隔；
    第二子确定模块，用于将所述第二时间间隔与预先设置的时间阈值进行比对，确定所述智能设备是否发生故障。
  13. 根据权利要求10所述的装置，其中，所述装置还包括：
    提示模块，用于当确定所述智能设备发生故障后，生成与所述故障对应的报警信息。
  14. 一种智能设备故障诊断***，其中，包括：
    智能设备，用于按照预先设置的时间间隔发送运行数据；
    无线网关，与所述智能设备无线连接，用于建立服务器与所述智能设备之间的通讯连接；
    所述服务器，与所述无线网关连接，用于通过所述无线网关获取所述智能设备的所述运行数据，并且，根据所述智能设备的所述运行数据，诊断所述智能设备是否发生故障。
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