JP2014066723A - Physical quantity data processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a physical quantity data processing program capable of generating a measurement data of a physical quantity associated with the measurement time even when a physical quantity measurement device has no function to count the present time.SOLUTION: The physical quantity data processing program makes a portable terminal having a communication function to function as a physical quantity data processing device, which has an exposed socket shape and includes data transmitting/receiving section using an infrared communication or radio waves, to perform communication with each of plural measurement devices that transmits a time sequence data while adding a piece of identification information and receives a data stored in each of the measurement devices. The physical quantity data processing program makes the portable terminal to function to obtain a piece of information on the present date and time as reception start time; to function to transmit a predetermined data transmission request to the measurement devices; and to function to generate a piece of information on the measurement time and to store the same together with the time sequence data of a measurement value transmitted from the measurement devices while adding the time information.

Description

  The present invention relates to a physical quantity data processing program that can be used for collecting information relating to physical quantities such as electric power, electric energy, temperature, humidity, and noise.

  For example, in order to reduce carbon dioxide emitted into the atmosphere or to reduce wasteful expenses, it is not used effectively among the power consumption of various electrical devices in homes and corporate offices. There is a demand for suppressing wasteful power consumption. In order to suppress such wasteful power consumption, it is first necessary to correctly grasp the actual situation. Therefore, for each electrical device used in the home or office, information indicating how much power is actually consumed at each time is measured continuously or periodically over a long period of time. The resulting data needs to be saved for later analysis.

  An apparatus that can be used for collecting such data is disclosed in Patent Document 1, for example. Patent Document 1 proposes a small power consumption measuring device that can be connected between a power plug of an electric device and a power outlet. That is, power data is calculated by periodically sampling the voltage and current supplied from the power outlet side to the electric equipment side via the small power consumption measuring device, and this data is stored in the memory. The small power consumption measuring device is equipped with a function for managing time and date.

  Patent Document 2 proposes a simple power amount display capable of displaying the power consumption of an electric device in real time. However, the simplified electric energy display of Patent Document 2 is not equipped with a function for saving data or a function for managing date and time.

JP-A-8-184616 JP 2000-147014 A

  In order for a user or administrator to correctly determine trends in the power consumption of each electrical device and the presence or absence of wasteful power consumption, the physical quantity such as the power of the electrical device is measured with a measuring device, and the measurement data It is necessary to generate data in association with the measurement date and time. For example, a relatively large amount of power is consumed by the electrical device even when the user is not using the corresponding electrical device effectively, such as when the user is absent or sleeping. In such a case, it can be determined that useless power consumption has occurred, and it can be considered that there is room for improvement.

  For example, if a measuring device disclosed in Patent Document 1 is used, data such as power including date and time information can be accumulated. However, since a measuring device such as that disclosed in Patent Document 1 needs to add and store date and time information to the measured power data, the calendar, timekeeping function, and time are adjusted inside the measuring device. It is indispensable to install an operation unit and the like. Therefore, the device cost of the measuring device is increased, and the user needs to perform an operation to set the time of the measuring device.

  In order to grasp the tendency of power consumption for each of a plurality of electrical devices in the home or office, a plurality of measuring devices that measure the power value of each electrical device are required. If the cost of one measuring device is high, it is expensive to use a plurality of measuring devices simultaneously.

  In addition, when using a plurality of measuring devices, if the user does not calibrate the time of each measuring device in advance, a relative time lag occurs between the data when the data acquired from each measuring device is aggregated. Therefore, accurate analysis cannot be performed.

  Note that the device disclosed in Patent Document 2 does not have a function of storing data or a function of managing date and time, and therefore cannot be used for collecting data necessary for analyzing a power consumption trend.

  An object of the present invention is to provide a physical quantity data processing program for realizing a physical quantity data processing apparatus capable of generating measurement data of a physical quantity associated with a measurement time even if the physical quantity measuring apparatus does not have a function of counting time. provide.

  The physical quantity data processing program of the present invention comprises a plurality of mobile terminals equipped with communication functions, each having an exposed outlet shape, including a data transmission / reception unit using infrared communication or radio waves, and adding identification information to time-series data. A physical quantity data processing program for functioning as a physical quantity data processing device that communicates with each of the measurement devices and receives data stored in the measurement device, and causes the portable terminal to receive information on the current date and time , A function for acquiring a data transmission request to the measurement device, a function for generating information on measurement time in the measurement device, and a measurement value sent from the measurement device And a function of adding information related to the measurement time to the time-series data and storing it.

  According to the above configuration, the physical quantity data processing program sends the data transmitted from each measurement device configured in a shape like an exposed outlet to the time-series data with identification information added to a mobile terminal equipped with a communication function. A function of functioning as a physical quantity data processing device to receive, a function of acquiring current date and time information as a reception start time, a function of transmitting a predetermined data transmission request to the measurement device, and a measurement time of the measurement device And a function of adding information related to the measurement time to the time-series data of measurement values sent from the measurement device and storing the information. For this reason, the physical quantity data processing program can communicate time series data of measured values measured by each measuring device to a mobile terminal while distinguishing each measuring device from a plurality of measuring devices. Information about the measurement time of the measurement value measured by the apparatus can be generated.

  The physical quantity data processing program is downloaded to the mobile terminal from an external communication equipment device.

  According to the above configuration, the physical quantity data processing program is used in the mobile terminal and can be downloaded from the external communication facility device to the mobile terminal.

  The physical quantity data processing program further causes the portable terminal to further realize a function of uploading time series data of the measurement value to which information related to the measurement time is added to an external server device.

  According to the above configuration, the physical quantity data processing program can cause the portable terminal to upload time-series data of measurement values to which information related to the measurement time is added to an external server device.

  The physical quantity data processing program further causes the portable terminal to further realize a function of generating measurement time information in the measurement device based on current date and time information as the reception start time. .

  According to the above configuration, the measurement time information given to the time series data is generated based on the current date information and time information managed by the current time management unit. Date information and time information need not be managed. Therefore, the device cost of the measuring device can be reduced. Further, the physical quantity data processing program may not calibrate the time on the mobile terminal side. When a system is configured by combining a plurality of measuring devices and one portable terminal, there is no relative shift in measurement time between data measured by the plurality of measuring devices.

  The physical quantity data processing program is based on the current date and time information as the reception start time and the measurement interval information of a predetermined physical quantity added together with the time series data by the measurement device. Further, a function of generating measurement time information in the measurement device is further realized.

  According to the above configuration, the physical quantity data processing program is accurate for each measurement value included in the time-series data, even when the predetermined interval at which the measurement device measures the predetermined physical quantity is not constant. Measurement time information can be generated.

  The physical quantity data processing program is based on the current date and time information as the reception start time and the measurement time difference information of a predetermined physical quantity added together with the time-series data by the measurement device. And a function of generating measurement time information in the measurement device, wherein the measurement time difference information represents a time difference from a last measurement time of a predetermined physical quantity in the measurement device to a transmission start time of the time-series data. It is characterized by that.

  According to the above configuration, the physical quantity data processing program can suppress an increase in time error between the measurement time information generated by the mobile terminal and the measurement time actually measured by the measurement device. That is, the timing at which the measurement device measures the physical quantity and the timing at which the measurement device starts sending time-series data are not synchronized, so a time difference occurs between them. In order to take this time difference into account, the physical quantity data processing program can cause the portable terminal to generate accurate measurement time information based on the current date information and time information and the time difference information.

  According to the physical quantity data processing program of the present invention, even if the portable terminal as the physical quantity processing device does not have a function of counting the current time, the physical quantity measurement data associated with the measurement time is generated. Can be made.

1 is a block diagram showing a configuration of a data processing system 1 according to an embodiment of the present invention. The figure which shows the usage example of the data processing system 1 shown in FIG. The figure which shows the measurement processing flow of the data processing part 16 in the measuring device 10. FIG. The figure which shows the data reception process flow of the data process part. The figure which shows the measurement time calculation process flow performed by step S26 of FIG. The schematic diagram which shows the specific example of the state transition of the data accumulate | stored on a measuring device. The schematic diagram which shows the specific example of the relationship between the reception data on the data processor, and the time information produced | generated. FIG. 8A is a diagram showing an operation process flow of the measurement apparatus 10 when the measurement interval is changed in the physical quantity data collection system 1, and FIG. 8B is a data process when the measurement interval is changed. The figure which shows the operation processing flow of the apparatus 20. FIG. The figure which shows an example of time series data in the case of changing a measurement interval. The schematic diagram which shows the specific example of a data structure in case a measurement interval is variable. The figure which shows the processing flow which thins out the data of the data processing part. The figure which shows the specific example of the state transition of the data accumulate | stored after the data thinning-out process shown in FIG. The flowchart which shows the specific example of the process for compressing automatically the data amount which a measuring device accumulate | stores. FIG. 14 is a schematic diagram illustrating a specific example of a state transition of data on a memory when the measurement device executes the process illustrated in FIG. 13. The flowchart which shows the specific example of the process for a measuring device to change a measurement interval automatically according to a condition. The schematic diagram which shows the specific example of the state transition of the data on a memory in case a measuring device performs the process shown in FIG. It is a flowchart which shows the specific example of the measurement time calculation process in a data processor. FIG. 18A is a diagram illustrating a state of a measurement time calculation process in the data processing unit 21 based on a measurement result of one measurement apparatus 10 (A). FIG. 18B is a diagram illustrating a state of measurement time calculation processing in the data processing unit 21 based on the measurement result of the other measurement apparatus 10 (B). The flowchart which shows the operation example by the side of the measuring device for reducing the difference | error of the produced | generated time. The flowchart which shows the operation example by the side of the data processor for reducing the difference | error of the produced | generated time. The schematic diagram which shows the specific example of the time information produced | generated when performing the process shown in FIG.19 and FIG.20. The flowchart which shows the operation example of the data processor for receiving the data of the newest measured value. The schematic diagram which shows the structural example of the time series data accumulate | stored on a measuring device.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram showing a configuration of a physical quantity data processing system 1 (hereinafter referred to as a data processing system 1) according to an embodiment of the present invention. As shown in FIG. 1, the data processing system 1 receives a physical quantity measuring device 10 (hereinafter referred to as a measuring device 10) for measuring the power consumption of an electrical device and data accumulated by the measurement of the measuring device 10. The physical quantity data processing device 20 (hereinafter referred to as the data processing device 20).

  As shown in FIG. 1, the measuring device 10 includes a power plug 11, an output outlet 12, a current transformer 13, a rectifying / smoothing circuit 14, an AD conversion unit 15, a data processing unit 16, and a data storage unit. A memory 17 and a data transmission / reception unit 18 are provided.

  When the measuring apparatus 10 is used, the power plug 11 is inserted into a general power outlet in the home to which commercial power (AC 100 V) is supplied. Further, the plug of the power cord of the electrical device to be measured is connected to the output outlet 12. That is, since the output outlet 12 is connected to the power plug 11 via the power line 19, the power plug 11, the power line 19, and the output outlet are connected to the electrical equipment to be measured from the household power outlet. The power supply power of AC100V is supplied via 12.

  A current transformer 13 is connected to the power supply line 19 in order to detect the power supply current flowing through the electrical device to be measured. On the output side (secondary winding) of the current transformer 13, a current proportional to the level of the alternating current flowing in the power supply line 19 flows. The rectifying / smoothing circuit 14 rectifies and smoothes the AC waveform in order to convert the AC current detected by the current transformer 13 into a DC level. Therefore, a direct current level proportional to the current consumed by the electrical device to be measured is obtained at the output of the rectifying / smoothing circuit 14. The AD converter 15 samples the DC level of the analog signal output from the rectifying / smoothing circuit 14 and converts it into a digital value.

  The data processing unit 16 is a control microcomputer, and controls the entire measuring apparatus 10 and performs data processing by executing a program prepared in advance. The operation of the data processing unit 16 will be described in detail later. The data processing unit 16 includes a timer for counting in units of seconds or minutes, but does not include functions such as a clock or a calendar.

  The data storage memory 17 is a semiconductor memory capable of writing and reading data, and stores time-series data of measured values measured by the control of the data processing unit 16. The data transmitter / receiver 18 performs wireless communication for data communication with the data processing device 20 as necessary. The data transmitter / receiver 18 is mainly used to transfer time-series data stored in the data storage memory 17 to the data processing device 20. For the communication of the data transmitter / receiver 18, for example, infrared rays or radio waves can be used.

The power necessary for the operation of the AD converter 15, the data processor 16, the data storage memory 17, and the data transmitter / receiver 18 is generated by a power supply circuit (not shown) based on the AC power supplied to the power plug 11. To do.
In addition, about the measuring device 10 shown in FIG. 1, the rectification smoothing circuit 14 can also be abbreviate | omitted. In that case, the instantaneous value of the current is sampled a plurality of times within one cycle of the AC power supply waveform, and the effective value of the AC current is obtained from the plurality of current data by the arithmetic processing of the data processing unit 16.

  Note that the measuring apparatus 10 shown in FIG. 1 is configured assuming that the voltage of the AC power supply is constant (AC 100 V). However, when the fluctuation of the voltage of the AC power supply is large or when high measurement accuracy is required, the measuring device 10 can be equipped with a function for measuring the AC power supply voltage appearing on the power supply line 19.

Note that the measuring apparatus 10 shown in FIG. 1 can hold identification information (ID). For example, the data processing unit 16 adds the identification information (ID) of the actually measured measuring device 10 to the time series data measured by the plurality of measuring devices 10. Thereby, the data processing device 20 can identify which measurement device 10 measures the time-series data.

  On the other hand, the data processing device 20 shown in FIG. 1 includes a data processing unit 21, a calendar / time management circuit 22, a data transmission / reception unit 23, an operation unit 24, a display unit 25, and a data storage memory 26. I have.

  The data processing unit 21 is configured by a microcomputer, and controls the entire data processing device 20 and processes necessary data by executing a program prepared in advance. The operation of the data processing unit 21 will be described later in detail.

  The calendar / time management circuit 22 is composed of an integrated circuit and has a function of counting time in seconds. The calendar / time management circuit 22 manages information representing the current date and day of the week, and information representing the current time (hour, minute, second). Based on the control by the data processing unit 21, the calendar / time management circuit 22 initializes or calibrates information representing the current date and day of the week managed, and information representing the current time (hour, minute, second). You can do it.

The data transmission / reception unit 23 has a function of performing wireless communication with the measurement apparatus 10. The data transmitter / receiver 23 receives time-series data obtained by measurement from the measurement device 10. The data transmitter / receiver 23 uses, for example, infrared rays or radio waves in wireless communication with the measuring device 10.
In FIG. 1, only one measuring device 10 is shown, but the data transmitting / receiving unit 23 can perform wireless communication with a plurality of measuring devices 10. In this case, identification information (ID) that is independent from each other is assigned to each of the measurement devices 10, and the identification information assigned to each measurement device 10 is added to the time-series data transmitted by the measurement device 10.

  The operation unit 24 is equipped with switches such as a plurality of push buttons that are input by the user. For example, in order to calibrate information indicating the current date and day of the week managed by the calendar / time management circuit 22 and information indicating the current time (hour, minute, second), an operation based on a user input operation is performed. The unit 24 gives an instruction to the data processing unit 21.

  The display unit 25 has a function of displaying character information such as numerical values and graphs. For example, the display unit 25 displays information included in the time series data received by the data processing device 20 from the measurement device 10, for example, date and time.

  The data storage memory 26 is composed of, for example, a nonvolatile memory capable of writing and reading. The data transmission / reception unit 23 is used to store the time-series data received from the measuring apparatus 10 and the data after processing by the data processing unit 21.

  A usage example of the data processing system 1 shown in FIG. 1 will be described with reference to FIG. FIG. 2 is a schematic configuration diagram of a physical quantity data collection system 2 (hereinafter referred to as a data collection system 2) for collecting physical quantity measurement data using the data processing system 1 shown in FIG. The data collection system 2 includes a plurality of measurement devices 10 (A), 10 (B), 10 (C), 10 (D),... Further, in the data collection system 2 shown in FIG. 2, the analysis device 30 for analyzing the time series data including the identification information (ID) of each measurement device collected in the data processing device 20 includes the measurement device 10 and the data processing device. 20 is provided separately.

  For example, when it is desired to simultaneously monitor the power consumption state of various electric devices in a home for a long period of time in the home, the measuring device 10 that independently uses the electric power consumed by a large number of electric devices that are located at a distance from each other. Measure each. Therefore, a plurality of measuring devices 10 (A), 10 (B), 10 (C), 10 (D),.

  In the data collection system 2, when a plurality of measuring devices 10 are used at the same time, the plurality of measuring devices 10 are distinguished on the data processing device 20 side. Accordingly, identification information (ID) that is independent from each other is assigned to each of the measurement devices 10, and the identification information assigned to the measurement device 10 is added to time-series data transmitted by the measurement device 10.

  In the data collection system 2, each measuring device 10 is configured in the shape of an exposed outlet. The data transmitter / receiver 18 of each measuring device 10 employs infrared communication (IrDA).

  The data processing device 20 is composed of a mobile phone terminal, a portable personal computer, a portable information terminal (PDA) and the like equipped with an infrared communication function. It is possible to communicate with each of the plurality of measuring devices 10 (A), 10 (B), 10 (C), 10 (D),.

  In the data collection system 2, the data processor 20 is an independent analyzer 30 for analyzing the data collected from the measuring devices 10 (A), 10 (B), 10 (C), 10 (D),. Is used. As the analyzer 30, a personal computer or a PDA is used. In order to move the measurement data necessary for analysis from the data processing device 20 to the analysis device 30, for example, a removable and portable memory card 31 is used.

  The program used by the data processing device 20 can be downloaded from the communication facility of the mobile phone company to the data processing device 20, and the data measured and accumulated by the data processing device 20 is stored in the mobile phone company. It can also be uploaded to the server 32 via a communication facility. Similarly, a program used by the analysis device 30 for analysis or the like can be downloaded from the server 32 via the Internet 33 and used.

  Next, the measurement operation of the measurement apparatus 10 will be described with reference to FIG. FIG. 3 is a diagram illustrating a measurement process flow of the data processing unit 16 in the measurement apparatus 10.

  In step S11, the data processing unit 16 of the measuring apparatus 10 initializes (deletes all) the storage contents of the data storage memory 17. In step S12, the data processing unit 16 controls the AD conversion unit 15 which is a measurement circuit unit, performs sampling of measurement values (current values) necessary for power calculation at predetermined intervals, and converts the current transformer 13, rectifying and smoothing. The measurement value is converted in accordance with the characteristics of the circuit 14 and the AD conversion unit 15, and the data of the current value flowing through the power supply line 19 is acquired.

In step S13, the data processing unit 16 obtains desired data by appropriately processing the current value data acquired in step S12. In the case of the present embodiment, the measured value of power corresponding to the current value measured at a predetermined interval is obtained by calculating the product of one current value converted to DC and a constant (100 V) corresponding to the power supply voltage. can get.

  In step S <b> 14, the data processing unit 16 stores the data of the power measurement value acquired in step S <b> 13 as time series data on the data storage memory 17. That is, data such as electric power obtained every time it is measured at a predetermined interval is arranged in the order of the measured time and stored as time series data. Here, since the data processing unit 16 does not have a function for managing time, the data stored in the data processing unit 16 does not include measurement time information regarding the measurement time.

In step S <b> 15, the data processing unit 16 monitors the state of the data transmission / reception unit 18 and identifies whether or not a data transmission request has been received from the data processing device 20 in a state where communication with the measurement device 10 is possible. . If a data transmission request is received, the process proceeds to step S16. If not received, the process proceeds to step S20.

In step S <b> 16, the data processing unit 16 transmits all the time-series data stored in the data storage memory 17 so far to the data processing device 20 in order via the data transmission / reception unit 18.
In step S <b> 17, the data processing unit 16 monitors the reception state of the data transmission / reception unit 18 and identifies whether or not a predetermined reception completion signal has been received from the partner data processing device 20. If a reception completion signal has been received, the process proceeds to step S18; otherwise, the process proceeds to step S19.

  In step S18, the time-series data transmitted in step S16 is deleted from the data storage memory 17. By erasing data, a new writable storage area on the data storage memory 17 is increased. That is, since data that has been transmitted is managed on the data processing device 20 side, there is no need to leave data on the measuring device 10 side.

In step S19, since there is a possibility that data transmission has failed, the data processing unit 16 does not erase the data and holds the data as it is on the data storage memory 17.
In step S20, the data processing unit 16 monitors the state of the internal timer and waits for a predetermined time. When this waiting time is over, the process proceeds to step S12. That is, step S12 is executed according to the timing based on the count value of the internal timer in order to periodically sample the measurement value at every predetermined measurement interval (for example, every 60 seconds). Even when the measuring device 10 is transmitting the accumulated data in step S16, when the count value of the internal timer reaches the measurement interval, step S12 is executed and a new measurement value is acquired. .

  A specific example of the state transition of data stored in the data storage memory 17 by the measuring apparatus 10 is shown in FIG. Immediately after step S11 of FIG. 3 is executed, no data exists on the data storage memory 17. And whenever it performs step S12-14, the data of a new measurement value are accumulate | stored in order. That is, when data “a, b, c, d, e, f, g, h, i, j, k, l, m” is obtained in order as shown in FIG. “A, b, c, d, e, f, g, h, i, j” are stored in order from the old area on the memory 17 to the new area. When there is no remaining storage area, the stored data is sequentially shifted toward the old area, and the oldest data is discarded because there is no storage area. The next new data “k, l, m” is stored in the storage area that is newly vacated by the data shift. Normally, the measuring device 10 transmits data to the data processing device 20 before the data storage memory 17 is full of data.

Next, the data reception operation of the data processing device 20 will be described with reference to FIG. FIG. 4 is a diagram illustrating a data reception processing flow of the data processing unit 21.
To enable communication between the data processing device 20 and the measurement device 10 while the data processing device 20 is operating, and to receive measurement data on the data processing device 20 by a user operation, for example. When the program starts, the operation of the data processing unit 21 proceeds to the process of step S21.

In step S <b> 21, the data processing unit 21 acquires information on the current date and time from the calendar / time management circuit 22 as a reception start time.
In step S <b> 22, the data processing unit 21 controls the data transmitting / receiving unit 23 to transmit a predetermined data transmission request to the measuring device 10. When receiving the data transmission request, the measuring apparatus 10 starts data transmission in step S16.

In step S23, the data processing unit 21 of the data processing device 20 receives the time series data of the measurement values sent from the measurement device 10 via the data transmission / reception unit 23, and stores this data.
In step S24, the data processing unit 21 identifies whether or not all the time series data has been normally received without error in step S23. If it has been received normally, the process proceeds to step S25, and if not, the process returns to step S21.

In step S25, the data processing unit 21 transmits a predetermined reception completion signal to the measurement device 10 via the data transmission / reception unit 23, and notifies the measurement device 10 that reception of all time-series data has been successful.
In step S <b> 26, the data processing unit 21 generates information about the measurement time for the time series data received in step S <b> 23 and stores the data with the time information added in the data storage memory 26. Details of this processing (hereinafter referred to as measurement time calculation processing) will be described later.

In step S27, in order to enable analysis of the time-series data received from the measuring device 10, the data processing unit 21 activates an analysis program (data processing application) prepared in advance.
Next, the measurement time calculation process executed in step S26 of FIG. 4 will be described with reference to FIG. FIG. 5 is a diagram showing a measurement time calculation process flow executed in step S26 of FIG. A specific example of the relationship between the received data and the generated time information on the data processing device 20 is shown in FIG.

(Measurement time calculation process)
In step S31, the data processing unit 21 clears the value N of the internal counter of the data processing unit 21 used for specifying the data to be referred to.
In step S32, the data processing unit 21 acquires data representing the measurement interval. If the measurement interval does not change, a constant may be used as the measurement interval. If the measurement interval is variable, the measurement interval corresponding to the data to be processed is acquired from the received data, for example.

In step S33, the data processing unit 21 refers to the value N of the internal counter and acquires the Nth measurement value in order from the latest measurement value to the old measurement value in the received time series data.
According to the measurement time calculation processing flow shown in FIG. 5, for example, as shown in FIG. 7, “a, b, c, d, e, f, g, h” obtained by sequentially measuring at a fixed measurement interval. When the data processor 20 receives the data sequence as time-series data, the latest measured value “h” measured last among these data is first referred to as the 0th data. Since the value N of the internal counter is sequentially updated, every time step S33 is executed, the 0th data “h”, the first data “g”, the second data “f”, the third data “ e ”,... are sequentially referred to.

  If the processing of all received data has not been completed, the processing of the data processing unit 21 proceeds to step S34 after step S33. In step S34, the measurement time t of the Nth data (measurement value) acquired in step S33 is calculated by the following equation (1).

  The “reception start time” in the equation (1) is the time acquired from the calendar / time management circuit 22 in step S21 of FIG. Further, the “measurement interval” in the equation (1) is the value (for example, 60 seconds) acquired in step S32.

In the example of the time series data illustrated in FIG. 7, it is assumed that the “reception start time” is “14:20:30 on August 20, 2008” and the “measurement interval” is 1 minute. . That is, since the data processing unit 21 starts receiving time-series data immediately after acquiring the “reception start time”, the 0th data “h” that is the last measurement value is “reception start time”. The time information “14:20:30 on August 20, 2008” is assigned to the 0th data “h”. Further, since the “measurement interval” is 1 minute, the following time information is given to the data before that.
First data “g”: “14:19:30 on August 20, 2008”
Second data “f”: “14:18:30 on August 20, 2008”
Third data “e”: “14:17:30 on August 20, 2008”
Fourth data “d”: “14:16:30 on August 20, 2008”

In step S35, the data processing unit 21 assigns time information representing the measurement time t calculated in step S34 to each measurement value, and for example, data that associates the measurement value with the measurement time as shown in FIG. The data is stored on the storage memory 26.
In step S36, the value N of the internal counter is updated (added 1) in order to change the data to be referred to.

(Measurement interval change processing)
By the way, although the measuring apparatus 10 shown in FIG. 1 uses the power consumption of various electrical devices as a physical quantity to be measured, it is not limited thereto. For example, the measuring device 10 can measure other physical quantities such as temperature and humidity. The power consumption is likely to change in a short time, but the rate of change of temperature and humidity is relatively slow. Therefore, if the measurement interval is fixed to 1 minute according to the fluctuation speed of power consumption, when measuring temperature and humidity, the measurement is repeated at an interval shorter than necessary, and the memory capacity for storing data is reduced. It can be wasted. Further, even when the physical quantity to be measured is power consumption, the optimum measurement interval may change depending on the difference in the type and application of the electrical equipment to be measured.

  Therefore, the measurement apparatus 10 may be configured so that the measurement interval of the measurement apparatus 10 can be manually changed as necessary. For example, if an operation unit such as a switch is provided on the measurement apparatus 10 side, the operation unit can change the measurement interval by giving an instruction to the data processing unit 16 by a user's manual operation. However, if the operation unit is added, the measuring device 10 becomes larger, and it is inevitable that the cost of the entire system will increase if a large number of measuring devices 10 are used.

Therefore, an operation unit for changing the measurement interval may be provided in the data processing device 20 without being provided in the measurement device 10. Further, for example, an operation unit 24 shown in FIG. 1 can be used as an operation unit for changing the measurement interval.
Next, the operation process of the physical quantity data collection system 1 when changing the measurement interval of the measurement apparatus 10 will be described with reference to FIG. FIG. 8A is a diagram showing an operation processing flow of the measurement apparatus 10 when the measurement interval is changed in the physical quantity data collection system 1, and FIG. 8B is a diagram when the measurement interval is changed. 4 is a diagram illustrating an operation processing flow of the data processing device 20. FIG.

  Referring to FIG. 8B, the data processing unit 21 of the data processing device 20 monitors the state of the operation unit 24 to identify the presence / absence of an input operation of a measurement interval change instruction in step S45. When the input operation of the measurement interval change instruction is detected, the measurement interval is determined according to the content of the input operation in the next step S46.

  As a specific example, a plurality of numerical values, for example, 30 seconds, 1 minute, 5 minutes, 10 minutes, 30 minutes, etc. are prepared as candidates for the measurement interval, and are adopted whenever there is an input operation from these candidates. What is necessary is just to process by step S46 so that a numerical value may be switched sequentially.

  In step S47, the data processing unit 21 of the data processing device 20 transmits a measurement interval change command to the measuring device 10 via the data transmitting / receiving unit 23 together with the value of the retrial measurement interval determined in step S46.

  Referring to FIG. 8A, the data processing unit 16 of the measuring device 10 monitors the state of the data transmitting / receiving unit 18 and identifies whether or not a measurement interval change command has been received from the data processing device 20 in step S41. To do. When the measurement interval change command is received, the data processing unit 16 updates the measurement interval in accordance with the change command in step S42. When the update is completed, the data processing unit 16 transmits an update completion notification to the data processing device 20 via the data transmission / reception unit 18.

  When the measurement interval of the measurement device 10 is variable according to the operation processing flow shown in FIG. 8, if the data processing device 20 does not grasp the actual measurement interval in order to generate time information, the data processing device 20 Correct time information cannot be generated. Therefore, the time-series data transmitted by the measuring device 10 includes at least one value representing the measurement interval.

FIG. 9 is a diagram illustrating an example of time-series data when the measurement interval is changed. As shown in FIG. 9, “INTERVAL” representing the actual measurement interval is included in the head position of the time-series data transmitted by the measurement apparatus 10. Accordingly, the data processing unit 21 of the data processing device 20 can acquire “INTERVAL” of the measurement interval from the time series data received in step S32 of FIG. Then, the data processing unit 21 of the data processing device 20 can calculate the measurement time from the above-described equation (1). Therefore, the time information of each data is obtained as follows.
First data “g”: “• 14: 20: 30—“ INTERVAL ”× 1”
Second data “f”: “• 14: 20: 30−“ INTERVAL ”× 2”
Third data “e”: “• 14: 20: 30−“ INTERVAL ”× 3”
4th data “d”: “• 14: 20: 30−“ INTERVAL ”× 4”

  On the other hand, when there is a possibility that the measurement apparatus 10 frequently changes the measurement interval as in the case of switching the measurement interval in the middle of measurement, information on the measurement interval is obtained for each measurement value of the series of time series data. I need it. In that case, the time-series data transmitted by the measuring device 10 may be configured as in the example shown in FIG.

  In the example shown in FIG. 10, measurement interval information is added to each measurement value. That is, the time interval from the measurement of the data “g” to the measurement of the data “h” is measured for the data “g”, and the data “g” is measured after the measurement of the data “f” for the data “f”. The time interval until the measurement is performed, the time interval from the measurement of the data “e” to the measurement of the data “f” is measured for the data “e”, and the data “d” is measured for the data “d”. The time interval from the start to the measurement of the data “e” is added.

  Therefore, each time the data processing unit 21 of the data processing device 20 refers to the Nth measurement value in step S33 in FIG. 5, the data processing unit 21 acquires the corresponding measurement interval added to the Nth measurement value. The measurement time can be calculated from the following equation (2).

Therefore, the time information of each data is obtained from the equation (2) as follows.
First data “g”: “• 14: 20: 30”-“10 seconds”
Second data “f”: “• 14: 20: 20—“ 10 seconds ”
Third data “e”: “• 14: 20: 10—“ 10 seconds ”
Fourth data “d”: “• 14: 20: 00-“ 10 seconds ”
Fifth data “c”: “• 14: 19: 50—“ 30 seconds ”

(Data thinning process)
By the way, if the period during which the data stored in the measuring device 10 is not transmitted to the data processing device 20 becomes long, there will be no available memory for storing data. When the low-cost measuring device 10 is configured, a large-capacity memory cannot be used. Therefore, all the old data cannot be erased unless the storage area having a limited capacity is used effectively. In addition, old data that has passed a certain period of time (for example, several months) after measurement is necessary when analyzing a tendency over a long period of time, although the degree of importance is low. However, since it is only necessary to grasp an approximate trend for old data, detailed data is not necessary.

  Therefore, the data processing unit 16 of the measurement apparatus 10 performs a process of thinning data (hereinafter referred to as data thinning process) by deleting a part of past data. With reference to FIG. 11, the data thinning process of the data processing unit 16 will be described. FIG. 11 is a diagram showing a processing flow for thinning out data in the data processing unit 16. With this process, the amount of data stored in the measuring apparatus 10 can be automatically reduced. In addition, the limited storage area of the memory 17 of the measuring device 10 can be used effectively. In addition, the measurement device 10 can accumulate data for a long period of time. FIG. 12 shows a specific example of the state transition of data accumulated after the data thinning process shown in FIG.

  In step S51, the data processing unit 16 detects whether or not new data to be accumulated by measurement has been added to the data accumulation memory 17. If the addition is detected, the process proceeds to the next step S52. In step S52, it is identified whether or not the amount of data stored in the data storage memory 17 is greater than or equal to a predetermined value.

  The storage area on the data storage memory 17 is divided into, for example, a storage area A1 and a storage area A2 as shown in FIG. No special processing is performed while only the storage area A1 is used, but special processing is performed when data is stored in the storage area A2. That is, when the amount of accumulated data exceeds a predetermined value, it is considered that the accumulation area A2 is being used, and the process proceeds to step S53.

  In step S53, the data thinning process is performed by deleting only a part of the data in the storage area A2 in which the old data is stored. For example, as shown in FIG. 12, after the data “a, b, c, d, e, f, g, h, i, j, k” are stored in the storage area A1, “l, m, n When the data “, o, p” is further added, the previously accumulated data “a, b, c, d, e” moves to the storage area A2. In this case, step S53 is executed. Then, the data “a, b, c, d, e” existing in the storage area A2 is thinned out.

  In the example shown in FIG. 12, thinning is performed so that one of two adjacent data is deleted and the remaining one is left. That is, only a part of the data “a, c, e” in the thinning-out target data “a, b, c, d, e” remains in the accumulation area A2. As another example of thinning, it is also conceivable to perform processing so that an average value of two consecutive data is left as a processing result.

  Here, when the measurement device 10 performs the data thinning process illustrated in FIG. 11 on the accumulated data stored in the data storage memory 17, the measurement device 10 performs information on thinning of the accumulated data (for example, thinning is performed). Information for specifying the area and information regarding the thinned data amount) are managed. Then, the measuring device 10 includes information related to thinning of accumulated data in the header of time-series data to be transmitted to the data processing device 20. Therefore, the data processing device 20 can grasp the correct measurement date and time for the time-series data transmitted from the measuring device 10 after the thinning processing based on the information related to thinning of the accumulated data.

(Storage data compression processing)
Next, an operation when the measurement device 10 compresses the stored data in the data storage memory 17 and transmits the compressed data to the data processing device 20 will be described. The data transmission time to the data processing device 20 can be shortened by compressing the stored data before the measuring device 10 transmits the stored data to the data processing device 20. Further, the measuring device 10 can effectively use the limited storage area of the data storage memory 17. Here, with reference to FIG. 13, a process in which the data processing unit 16 compresses accumulated data (hereinafter referred to as accumulated data compression process) will be described. FIG. 14 shows a configuration example of data after the accumulated data compression processing shown in FIG.

In step S61, the data processing unit 16 searches the data stored in the data storage memory 17 for a data string in which the same values are continuously arranged (hereinafter referred to as a specific data string). Further, the data processing unit 16 identifies whether or not the specific data string is found in the next step S62, and if found, the process proceeds to step S63.
For example, when the data on the left side shown in FIG. 14 is stored in the data storage memory 17, eight “5” measurement values following “10” and “3” are detected as specific data strings. The

  In step S63, the continuous number of the same numerical value is counted about the specific data string found by the search of step S61. In the case of the data on the left side shown in FIG. 14, since the specific data string is formed by arranging eight measurement values of the same “5”, “8” is obtained as the continuous number.

  In step S64, the data processing unit 16 replaces the specific data string with compressed data. In the example illustrated in FIG. 14, a combination of a common measurement value “5” of a specific data string, a control symbol “*” (continuous identification value) indicating compressed data, and a continuous number “8” is compressed data. And With such compressed data, it is easy to restore the original data “5, 5, 5, 5, 5, 5, 5, 5” before compression. For example, when decompressing the compressed data received from the measurement device 10, the data processing device 20 identifies the presence or absence of the control symbol “*” from the received data, and if the control symbol “*” is included. A process of restoring the original data may be performed using the data before and after that.

In step S65, the data processing unit 16 identifies whether or not the processing of all data stored in the data storage memory 17 has been completed. If not, the process returns to step S61 and repeats the above processing.
For example, when measuring the power consumption of an electrical device, it may be possible that a state in which the power consumption hardly changes if the operating state of the electrical device does not change continues for a long time. In such a case, the memory consumption in the measuring apparatus 10 can be significantly suppressed by the data compression as described above.

(Measurement interval optimization process)
By the way, the optimal value of the measurement interval in the measurement apparatus 10 varies depending on, for example, the characteristics of the physical quantity to be measured. For example, in a situation where data is regularly transferred from the measuring device 10 to the data processing device 20, there is no problem that past data obtained by measurement is deleted due to insufficient memory. It is better to shorten the measurement interval. However, in a situation where data is not transferred for a long time, it is better to set a longer measurement interval to prevent old data from being erased. Also, in situations where measured values hardly change, it is better to set a longer measurement interval to prevent the accumulation of large amounts of low-use-value data, but situations where measured values fluctuate frequently. Then, by shortening the measurement interval, it is possible to obtain detailed data on data with high utility value.

  Therefore, in order to automatically change the measurement interval of the measurement device 10 in accordance with the situation, the data processing unit 16 of the measurement device 10 optimizes the measurement interval (hereinafter referred to as measurement interval optimization processing). To implement. The measurement interval optimization process performed by the data processing unit 16 will be described with reference to FIG. FIG. 15 is a diagram illustrating a flow of measurement interval optimization processing performed by the data processing unit 16. FIG. 16 shows a specific example of data stored in the data storage memory 17 in the measurement interval optimization process shown in FIG.

In step S71, the data processing unit 16 identifies whether a new measurement value has been input. That is, when new measurement values are obtained in steps S12 and S13 shown in FIG. 3, the process proceeds from step S71 to step S72.
In step S72, the data processing unit 16 compares the latest measured value with a predetermined threshold value THmin. As a result of the comparison, if both values satisfy the condition “latest measured value> THmin”, the process proceeds to step S73. If not, the process proceeds to step S74. For example, if the threshold value THmin is set to 50 W, it is possible to distinguish between a standby state and a normal operation state in which fluctuations in the power consumption of the electrical equipment are small.

  In step S73, the data processing unit 16 employs “T1: for example, 10 seconds” as a subsequent measurement interval. In step S74, the data processing unit 16 employs “T2: 60 seconds” as the subsequent measurement interval.

  In step S75, the data processing unit 16 detects the amount of stored data, that is, the total number of measurement values stored in the data storage memory 17 at that time (corresponding to the number of times of measurement of data remaining in the memory).

  In step S76, the data processing unit 16 compares the accumulated data amount detected in step S75 with a predetermined threshold value Dth. If the condition “accumulated data amount> Dth” is satisfied, the process proceeds to step S77. Otherwise, the process proceeds to step S78. As a specific example of the threshold value Dth, it may be set to the number of measurement values that consume half of the storage capacity of the data storage memory 17.

  In step S77, the data processing unit 16 employs “T3: 120 seconds” as the subsequent measurement interval. As a result, when the remaining amount of the data storage memory 17 is reduced, the measurement interval is automatically lengthened, and long-term data can be stored. For example, when the condition of step S76 is not satisfied, T1 or T2 may be adopted as the measurement interval, and when the condition of step S76 is satisfied, the measurement interval twice as long as T1 or T2 may be adopted. .

  In step S78, the data processing unit 16 stores the latest measurement value and the measurement interval value finally adopted in any of steps S73, S74, and S77 in the data storage memory 17 as a set of data.

  Here, in the example illustrated in FIG. 16, time-series data “10, 15, 1, 1, 0, 20, 25, 30,...” Exists as the measurement values measured in order. In this example, it is assumed that the threshold value THmin is “5” corresponding to 50 W. Therefore, for the first and second measurement values “10, 15”, T1 (= 10 seconds) is set in step S73. Adopting T2 (= 60 seconds) in step S74 for the third to fifth measurement values “1, 1, 0”, and for the sixth to eighth measurement values “20, 25, 30” In step S73, T1 (= 10 seconds) is adopted. Therefore, as shown in FIG. 16, for each of the measured values of “10, 15, 1, 1, 0, 20, 25, 30,...”, “10, 10, 60, 60, 60, 10, 10, 10,..., Is given, and the measurement value and the measurement interval are paired and stored on the data storage memory 17.

  Note that the threshold value THmin and the threshold value Dth may be appropriately determined according to the application. These threshold values can be made variable. For example, the threshold value may be changed by giving an instruction from the data processing device 20 to the measurement device 10. If a plurality of threshold values THmin to be compared in step S72 are prepared, the measurement interval can be switched to three or more types according to the magnitude of the measurement value. Further, if a plurality of threshold values Dth to be compared in step S76 are prepared, it is possible to switch the measurement interval to three or more types according to the remaining memory capacity.

(Modification of measurement time calculation process)
By the way, in the case where a plurality of measuring devices 10 and one data processing device 20 are used in combination as in the use example of the physical quantity data collection system 1 shown in FIG. There are times when the measurement time of the data is not aligned. Therefore, for example, when comprehensively analyzing data measured by a plurality of measuring devices 10, a time difference must be taken into account for the measurement times generated by the data processing device 20. Therefore, with reference to FIG. 18, the measurement time calculation process of the data processing unit 21 in the data processing device 20 when the measurement times of the data transmitted from the plurality of measurement devices 10 are not aligned will be described. FIG. 18A is a diagram illustrating a state of measurement time calculation processing in the data processing unit 21 based on the measurement result of one measurement apparatus 10 (A), and FIG. 18B is a diagram illustrating the other measurement apparatus 10. It is a figure which shows the mode of the measurement time calculation process in the data processing part 21 based on the measurement result of (B).

In the example shown in FIG. 18A and FIG. 18B, “Outlet 1” corresponding to the measuring device 10 (A) and “Outlet 2” corresponding to the measuring device 10 (B) are respectively powered at 1 minute intervals. Measure. Here, “Outlet 1” and “Outlet 2” operate asynchronously with each other. Therefore, as shown in FIGS. 18A and 18B, the measurement time of “Outlet 1” (for example, 14:21:05) and the measurement time of “Outlet 2” (for example, 14:21:10) ) Does not match.
Further, the measurement time generated by the data processing device 20 is generated with reference to the time at which data reception is started, but the data processing device 20 simultaneously starts receiving data for data of a plurality of measurement devices 10. is not. For example, when data reception from “Outlet 1” is started at “14:21:20” and data reception from “Outlet 2” is started at “14:21:50”, the data processing apparatus 20 side “ The measurement times given to the last measurement values of “Outlet 1” and “Outlet 2” are “14:21:20” and “14:21:50”, respectively. Therefore, data with a measurement time of “..hours..minutes 20 seconds” and data with “..hours..minutes 50 seconds” are mixed on the data processing device 20 side. Management becomes complicated.

  Therefore, the data processing unit 21 of the data processing device 20 executes the process shown in FIG. 17 in order to generate data whose measurement time can be easily managed. The process shown in FIG. 17 is a modification 1 of the measurement time calculation process shown in FIG. Here, the modification of the measurement time calculation process shown in FIG. 17 is different from the measurement time calculation process shown in FIG. 5 in that step S37, step S38, and step S36 are performed instead of step S35 and step S36 shown in FIG. There is S39. Hereinafter, of the steps shown in FIG. 17, step S37, step S38, and step S39 that are different from the step shown in FIG. 5 will be described, and description of the other common steps S31 to S34 will be omitted.

  In step S37, the value of the second digit is processed as a fraction for the measurement time t calculated in step S34, and is corrected to the reference time. For example, assuming that the reference time is “00 seconds”, as shown in FIGS. 18A and 18B, data reception from “Outlet 1” that started receiving data at “14:21:20” is performed. For the last measured value of the data, the “outlet” that started receiving data at “14:21:50” when the second digit was corrected to “00 seconds” was “14:21:00” The last measured value of the data from “2” is the measurement time “14:21:00” with the second digit corrected to “00 seconds”. That is, the measurement times added to the measured values of “Outlet 1” and “Outlet 2” are aligned with each other. Therefore, when analyzing a plurality of data while comparing the times, it is not necessary to consider the time difference between the fractions of the times.

  For the reference time, in addition to “00 seconds”, a value in units of 10 seconds such as “00 seconds + (10 × M) seconds” (M: 0, 1, 2, 3, 4, 5), It is also conceivable to adopt a value in units of 30 seconds such as “00 seconds + (30 × M) seconds” (M: 0, 1). In addition to rounding down, rounding up and rounding can be considered for rounding.

  In step S38 in FIG. 17, the measurement time t corrected in step S37 is stored in the data storage memory 17 together with the measurement value. Therefore, even when using a plurality of measuring devices 10 that operate asynchronously with each other, the data processing device 20 can store data with the same measurement time.

  Incidentally, the measurement time generated by the data processing device 20 is determined in synchronization with the time when data reception from the measurement device 10 is started, but the time when the data processing device 20 starts data reception is irregular. Therefore, if the time difference from when the measurement device 10 measures the latest measurement value to when the data processing device 20 starts to receive data becomes longer, the time between the measurement time generated by the data processing device 20 and the actual measurement time is increased. The time error increases. The control on the measurement device 10 side and the control on the data processing device 20 side which are executed to reduce the time error of the measurement time are shown in FIGS. A specific example of the operation state of the measuring device 10 and the data processing device 20 is shown in FIG.

  First, the operation of the data processing unit 16 on the measurement apparatus 10 side will be described with reference to FIG. In step S81, the data processing unit 16 identifies whether or not it is time to measure a new measurement value. That is, when it is time to execute step S12 shown in FIG. 3, the process proceeds from step S81 to step S82.

  In step S82, the data processing unit 16 clears the count value of the internal timer TM and starts its operation. For the internal timer TM, for example, a timer capable of counting in units of 1 second is assumed.

  In step S83, the data processing unit 16 monitors the state of the data transmission / reception unit 18 and identifies whether or not a data transmission request from the data processing device 20 has been detected. That is, before starting transmission of accumulated data in step S16 in FIG. 3, the process in step S84 in FIG. 19 is executed.

  In step S84, the data processing unit 16 refers to the counting time of the internal timer TM and acquires this time as the time difference Tout. In the next step S85, the data processing unit 16 adds the time difference Tout acquired in step S84 to the transmission data and transmits it. Therefore, the accumulated data transmitted in step S16 in FIG. 3 includes information on the time difference Tout.

  Next, the operation of the data processing unit 21 on the data processing apparatus 20 side will be described with reference to FIG. The operation shown in FIG. 20 is a second modification of the measurement time calculation process shown in FIG. Similarly to the operation shown in FIG. 5, the data processing unit 21 clears the counter value N in step S91, and acquires the value of the measurement interval in the next step S92.

In step S93, the data processing unit 21 acquires information on the time difference Tout included therein from the received time series data.
Similar to the operation shown in FIG. 5, the data processing unit 21 acquires the Nth measurement value in step S94, and calculates the measurement time t for this measurement value in step S96 using the following equation (3).

  Here, the “reception start time” in the expression (3) is the time acquired from the calendar / time management circuit 22 in step S21 of FIG. Further, the “measurement interval” in the equation (3) is the value (for example, 60 seconds) acquired in step S92.

  About the operation | movement of the data processing part 21 other than the above, it is the same as the case of the measurement time calculation process shown in FIG. Therefore, for example, in the example shown in FIG. 21, when the data processing device 20 starts receiving data at the time “14:21:10”, this received data includes the actual measurement time of the last measured value (E). A time difference (5 seconds) between “14:21:05” and “14:21:10” of the reception start time is included as Tout. Therefore, in the data processing device 20, when generating the measurement time of each measurement value from the received data, the accurate measurement time “14:21” from the reception start time “14:21:10” according to the equation (3). "05 minutes" can be calculated. In particular, when the measurement interval of the measurement apparatus 10 is long, the time difference Tout tends to increase. Therefore, the processes of FIGS. 19 and 20 are effective in order to reduce the error in the measurement time generated on the data processing apparatus 20 side. is there.

  By the way, when a large amount of time-series data is transferred from the measuring device 10 to the data processing device 20 once, or when the transmission speed at the time of communication is low, the time required for transferring all the data become longer. Therefore, the measurement apparatus 10 samples a new measurement value even during the data transfer, and accumulates the data of the measurement value in the data storage memory 17. However, since data measured after starting data transfer is not subject to transfer, the data processing device 20 may not be able to acquire the latest measured value.

  Therefore, the data processing unit 21 of the data processing device 20 performs the operation shown in FIG. 22 in order to obtain the latest measurement value. The operation shown in FIG. 22 is a modification of the operation shown in FIG. A specific example of the operation of the measuring apparatus 10 is shown in FIG. The operation shown in FIG. 22 will be described below.

  As in the case of the process shown in FIG. 4, the data processing unit 21 of the data processing device 20 acquires the date and time at the start of reception in step S101 of FIG. 22, and transmits a transmission request for accumulated data in step S102. Then, the time series data obtained by the measurement in step S103 is received from the measurement apparatus 10, and whether or not the reception has been normally completed is identified in step S104.

  When the reception of all the time series data transmitted at one time ends normally, the processing of the data processing unit 21 proceeds from step S104 to step S105. In step S <b> 105, the data processing unit 21 transmits a transmission request related to untransmitted accumulated data to the measurement apparatus 10 via the data transmission / reception unit 23.

  On the measurement device 10 side, after transmitting the accumulated data in step S16 shown in FIG. 3, when the transmission request from the data processing device 20 is received again, the presence or absence of untransmitted data is identified on the data accumulation memory 17. If there is untransmitted data, the corresponding data is transmitted to the data processing device 20.

  The data processing unit 21 of the data processing device 20 receives the remaining data transmitted from the measurement device 10 in response to the transmission request in step S105 in the next step S106. In step S107, the data processing unit 21 identifies whether or not the data reception in step S106 has been completed normally. If it is not a normal end, the process returns to step S101. If it is a normal end, the process proceeds to step S108.

  In step S108, the data processing unit 21 transmits a reception completion signal to the measurement apparatus 10 as in step S25 of FIG. In step S109, the measurement time calculation process, that is, the same process as in step S26 of FIG. 4 is executed.

  When the data processing device 20 sends a data transmission request at a certain point in time, as shown in FIG. 23, for example, all of the “accumulated data 1” accumulated in the data storage memory 17 of the measuring device 10 up to that point of time It is transmitted from the measuring apparatus 10 as “Communication 1”. If the time required for the operation of the “communication 1” is long, the measurement values “A, B, C” are newly sampled and accumulated in the data storage memory 17 during that time. Since the new measurement values “A, B, C” are accumulated after “communication 1” is started, “communication 1” is not included in the transmission target.

  Therefore, when the data processing device 20 requests data transmission again in step S105 after the operation of “communication 1” is completed, the measuring device 10 has not yet transmitted “accumulated data 2” including “A, B, C”. These are regarded as remaining data, and these are transmitted to the data processing device 20 by “communication 2”. Therefore, by performing “communication 2”, the data processing device 20 can also receive the data of the measurement value of “C” measured last.

  For example, when data with a capacity of 100 kB is transmitted from the measuring apparatus 10 to the data processing apparatus 20 at a communication speed of 10 kB / bps, the time required for communication is about 10 seconds. Therefore, for example, when the measurement interval is 3 seconds, about three measurement values are newly accumulated before the operation of “communication 1” is completed. Since “communication 2” has a small amount of data to be transmitted, the communication can be completed in a short time, and no new measurement value is accumulated on the measurement apparatus 10 during that time.

  In the above-described embodiment, the physical quantity to be measured is the power consumption of the electrical device. However, for example, temperature, humidity, noise, and the like can be measured as similar physical quantities.

1 physical quantity data processing system 2 physical quantity data collection system 10 physical quantity measuring device (measuring device)
DESCRIPTION OF SYMBOLS 11 Power plug 12 Output outlet 13 Current transformer 14 Rectification smoothing circuit 15 AD conversion part 16 Data processing part 17 Data storage memory 18 Data transmission / reception part 19 Power supply line 20 Physical quantity data processing apparatus (data processing apparatus)
21 Data Processing Unit 22 Calendar / Time Management Circuit 23 Data Transmission / Reception Unit 24 Operation Unit 25 Display Unit 26 Data Storage Memory 30 Analyzer 31 Memory Card 32 Server 33 Internet

Claims (6)

A mobile device equipped with a communication function
Consists of an exposed outlet shape, equipped with a data transmission / reception unit using infrared communication or radio waves, communicates with each of a plurality of measuring devices that add identification information to time series data, and transmits the data stored in the measuring device A physical quantity data processing program for receiving and functioning as a physical quantity data processing device,
In the mobile terminal,
A function of acquiring information on the current date and time as a reception start time;
A function of transmitting a predetermined data transmission request to the measuring device;
A function of generating information about a measurement time in the measurement device;
Realizing a function of adding information related to the measurement time to the time-series data of measurement values sent from the measurement device,
A physical quantity data processing program. The physical quantity data processing program according to claim 1,
The physical quantity data processing program is downloaded from an external communication equipment device to the mobile terminal.
A physical quantity data processing program. The physical quantity data processing program according to claim 1,
Further realizing the function of causing the portable terminal to upload the time series data of the measurement value to which information related to the measurement time is added to an external server device,
A physical quantity data processing program. The physical quantity data processing program according to claim 1,
Further realizing the function of generating measurement time information in the measurement device based on the current date and time information as the reception start time in the portable terminal,
A physical quantity data processing program. The physical quantity data processing program according to claim 1,
The measurement time in the measurement device based on the current date and time information as the reception start time and the measurement interval information of a predetermined physical quantity added together with the time series data by the measurement device to the portable terminal To further realize the function of generating information,
A physical quantity data processing program. The physical quantity data processing program according to claim 1,
Based on the current date and time information as the reception start time and the measurement time difference information of a predetermined physical quantity added together with the time series data by the measurement device to the portable terminal, the measurement time in the measurement device Further realize the function of generating information,
The measurement time difference information represents a time difference from the last measurement time point of the predetermined physical quantity in the measurement device to the transmission start time point of the time series data.
A physical quantity data processing program.

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