Monitoring systems for conveyor systems

Abstract

A monitoring system for a conveyor system, comprising: a pressure sensor mounted on a conveyor device; an accelerometer mounted on the conveyor device; and a controller arranged to: acquire accelerometer data by sampling the accelerometer; store the accelerometer data in a buffer; acquire the pressure sensor data by sampling the pressure sensor; determine from the pressure sensor data that a start or stop of the conveyor device has occurred; and analyze the accelerometer data to determine a first position within the accelerometer data when the determination is made, wherein the first position is the position at which the start or stop of the conveyor device occurred. Both the pressure and acceleration readings are combined to determine a point in time at which motion started or stopped. The pressure sensor is first used to determine a robust indication that a change in motion state has occurred (started or stopped). When the determination is made, the accelerometer data is then analyzed to make an accurate determination of the time of the change in motion state (i.e., the time at which the conveyor device started or stopped).

Description

Technical Field

[0001] The present disclosure relates generally to conveyor systems and, more particularly, to methods and apparatus for monitoring the movement of conveyor devices, particularly the direction of movement and / or start and / or stop times of conveyor devices within a conveyor system. Background Art

[0002] It is known to monitor the direction and position of movement of conveying equipment within conveying systems, such as, for example, elevator systems, escalator systems, and moving walkways. Typically, the position and direction can be determined using various position determining mechanisms, such as a rotary encoder in the drive system or an encoded magnetic tape with a corresponding magnetic tape reader (e.g., mounted on the elevator car) provided along the length of the conveying system (e.g., along the length of the hoistway in an elevator system). Position in an elevator system can also be detected using vanes installed in the hoistway (e.g., near a landing) and light sensors on the car (the light sensors are interrupted by the presence of the vanes). Summary of the invention

[0003] According to a first aspect of the present disclosure, there is provided a monitoring system for a transport system, comprising:

[0004] A pressure sensor mounted on the conveying device;

[0005] an accelerometer mounted on the transport device; and

[0006] A controller arranged to:

[0007] Acquiring accelerometer data by sampling the accelerometer;

[0008] storing accelerometer data in a buffer;

[0009] acquiring pressure sensor data by sampling the pressure sensor;

[0010] determining from the pressure sensor data that starting or stopping of the conveyor device has occurred; and

[0011] In the determining, the accelerometer data is analyzed to determine a first location within the accelerometer data, wherein the first location is a location where a start or stop of the transport device occurs.

[0012] Accurate determination of the motion of a conveying device (e.g., direction of travel and whether it is moving) can be difficult and / or costly. This is particularly true in systems where direct access to the drive machinery is not possible and the direction and position of the motion of the conveying device must be determined indirectly. This may be the case, for example, in condition-based maintenance systems that may be retrofitted to an earlier conveying system without being communicatively connected to the drive and / or control system. Such systems operate off of individual sensors that may be powered separately (e.g., by a battery or energy harvesting system) and use wireless communication to transmit diagnostic and / or analytical data to a monitoring server. The monitoring server may be located locally (on-site) or externally (off-site) (e.g., a cloud-based server).

[0013] Such condition-based maintenance detectors typically employ sensors that detect various characteristics of the transport system. For example, they may include accelerometers that are used to detect vibration signatures associated with certain operations, which can be compared with expected vibration signatures to determine whether those operations are functioning correctly. In addition, microphones can detect sound signatures associated with certain operations and / or faults, and light sensors can determine lighting characteristics and faults. Accelerometers may be provided as part of an inertial measurement unit (IMU), which also includes a gyroscope. Although such sensors typically include vertical accelerometers (i.e., accelerometers oriented to sense acceleration along a vertical axis), it is difficult to directly use such sensors to determine when a transport device starts and stops moving. The raw sensor data may be noisy and is typically sampled at a low rate (to save power), making accurate detection of acceleration associated with the start or stop of movement not straightforward. In addition, the signal processing required to detect the start or stop from accelerometer data alone is typically intensive and consumes considerable power, which is particularly unattractive in a separately powered device. On the other hand, by giving a simple and well-defined output indicating a significant change in pressure (altitude) or an insignificant change in pressure (altitude), the pressure sensor provides a robust indication that the motion has changed, such as when the motion has started or stopped. It will be appreciated that in the short period of time in which the transport system starts and stops motion, the pressure and altitude are substantially equivalent because the atmospheric pressure changes (e.g., caused by changing weather systems) are on a much slower scale. Although the pressure sensor is robust and easily measurable, it is still imprecise in establishing the time of the motion change. The accuracy of the readings from the pressure sensor can be approximately plus or minus 0.5 meters, so that a change in altitude of at least this magnitude (and preferably greater) must be used to establish a reliable indication of motion. Even if the pressure sensor samples at a high sampling rate, the accuracy of the readings prevents the accurate calculation of the time when the motion actually starts or stops.

[0014] Determining the precise time at which motion starts or stops is important for analyzing the behavior and characteristics of the system, and therefore can be important to aid in proper analysis of sensor information in a condition-based maintenance system. For example, accelerometer readings on an elevator while the elevator is stationary at a landing indicate the behavior and characteristics of the door as it opens and closes. On the other hand, those same accelerometer readings while the elevator is in motion between landings indicate the health of the car drive and guide systems, such as rollers and guide rails. The time between the door closing and the elevator car starting to move is short (in order to minimize passenger travel time), so it is important to be able to separate the door acceleration data from the car acceleration data by determining the time when the car starts to move. If an inaccurate estimate of the time at which car motion starts is made, car vibrations may be incorrectly attributed to door health, or door vibrations may be incorrectly attributed to roller or guide rail health (for example). The same situation applies when the elevator car stops moving, except that in some elevator systems the doors may start opening even before the elevator has stopped moving (called "advanced door opening"), so that there may even be some overlap where the detected acceleration may be attributable to the doors and the car.

[0015] According to the present disclosure, both pressure and acceleration readings are combined to determine the point in time when motion starts or stops. The pressure sensor is first used to determine a robust indication that the motion state has changed (started or stopped). When making the determination, the accelerometer data is then analyzed to make an accurate determination of the time of the change in motion state (i.e., the time when the transport device started or stopped). The processing required to extract the precise start or stop time from the accelerometer data is very intensive and power consuming, making it impossible to run continuously on a low-power (e.g., battery-powered or energy-harvesting) device. However, the pressure sensor detection portion of the process is low power and is used to trigger the accelerometer processing only when needed, making the overall detection process energy efficient and accurate.

[0016] It will be appreciated that the determination of the time at which the motion of the conveying device starts or stops can be an absolute time or a relative time. The time can be relative to the time at which the accelerometer analysis is triggered (i.e., the time at which the controller determines from the pressure sensor data that the start or stop has occurred). This can conveniently be expressed in terms of the number of samples in the accelerometer data (e.g., an index within a buffer). Such a measurement can of course be readily converted to an actual time measurement using a known sampling rate.

[0017] Determining the start or stop of a transport device from a pressure sensor may simply require noticing a change in pressure. However, occasional small changes in pressure may trigger small changes without indicating a change in movement. Therefore, in some examples, the controller is arranged to determine that the start or stop of a transport device has occurred based on detecting a change in pressure data of at least a threshold amount within a predetermined time period. For example, it may be required that a pressure change corresponding to at least 1.5 meters be considered significant within a time period of 4 seconds. Of course, these amounts are given as examples only. The threshold may be selected to be large enough to make false positive motion detections unlikely, while being small enough to enable rapid detection of changes, which minimizes the amount of accelerometer data that needs to be buffered.

[0018] The controller may be arranged to analyze any appropriate amount of accelerometer data or even all available data. However, in some examples, the controller is arranged to analyze the most recent time window of accelerometer data. The most recent time window may be the most recent accelerometer sample, i.e., a predetermined number of samples starting from the most recent sample and extending backward through the length of the defined window. The window may be the same size as the buffer so that the window contains all the data in the buffer, or it may be a subset of the buffer. In some examples, the window starts at the most recent accelerometer sample, but this need not be the case, because the delay in determining the change in motion through the pressure sensor may mean that the start or stop will occur a few seconds earlier, so that the portion of the most recent accelerometer sample may not be required for processing. The length of the window may be selected to be long enough to provide reliable identification of the change in motion, but short enough to keep the processing fast and energy-saving. In some examples, the most recent time window may have a length of at least 20 samples, or at least 30 samples, or at least 50 samples. In some examples, the time window may have a length of no more than 200 samples, or no more than 150 samples, or no more than 100 samples. However, it will be appreciated that in other examples, a higher sampling rate may be used, and the time window may have a greater length, such as a total of 1000 samples or more. The time length of the window will more generally depend on the number of samples and the sampling rate. In some examples, the time length of the most recent time window is at least 2 seconds, or at least 3 seconds, or at least 4 seconds. In some examples, the time window is no more than 10 seconds, or no more than 8 seconds, or no more than 6 seconds. In some examples, the time window may be any desired time length.

[0019] Depending on the nature of the accelerometer data, it may be possible to identify changes in motion without filtering the data. However, accelerometer data is usually noisy, which complicates analysis. The acceleration caused by the change in the motion of the transport equipment is usually smooth and changes at a very low frequency in order to provide a smooth and comfortable ride for passengers. Therefore, in some examples, the controller is arranged to filter the accelerometer data using a low-pass filter. The low-pass filter can be selected to cut out all or most of the noise, leaving only low-frequency acceleration data related to the main driving motion of the transport equipment. The low-pass filtered data can then be used in subsequent processing to determine the location where the start or stop occurs within the data. The low-pass filter requires moderately intensive processing, and it is therefore desirable not to run this low-pass filter continuously during operation, but only when the pressure sensor detects a change in motion. In addition, when the processing of high-frequency data is expected for other purposes (such as health analysis and / or condition-based maintenance), the continuous operation of the low-pass filter will require the storage (buffering) of two data sets (one high frequency, one low frequency). By using the pressure sensor as a trigger for start / stop analysis, low-pass filtered data can be generated and processed only in response to the trigger rather than requiring continuous buffering itself. The low-pass filter can be steep and ultra-low pass so as to focus only on acceleration due to the drive profile. In some examples, the low-pass filter may have a cutoff frequency of no more than 5 Hz, or no more than 3 Hz, or no more than 1 Hz. In some examples, the low-pass filter may be at least a second-order filter. In some examples, the low-pass filter may use forward-backward filtering (it may filter from the first sample to the last sample and then filter again from the last sample to the first sample). This avoids changing the phase of the signal. The low-pass filter may be a linear phase filter (which generates a constant delay) or a zero phase delay filter. The filter may be a Butterworth filter.

[0020] It will be appreciated that the drive profile may involve acceleration in a particular known direction such that only accelerometer data for that direction is considered. For example, in a vertical transport system (e.g., an elevator system), the motion trajectory is a vertical motion trajectory, and therefore the accelerometer data analyzed for starts and / or stops may consist of only vertical accelerometer data. It will be appreciated that the sensor may include accelerometers oriented in multiple directions (e.g., three mutually orthogonal directions) to have full three-dimensional acceleration sensing capabilities. This may be beneficial for detailed health analysis of vibrations. However, the accelerometer data used to detect the start and / or stop of the transport equipment may be the vertical component of that three-dimensional data. The accelerometer(s) may be an integral part of an inertial measurement unit.

[0021] In some examples, the controller is arranged to analyze the accelerometer data to find a second position within the accelerometer data, the second position being the position where the accelerometer data crosses a threshold, and wherein the controller is arranged to determine the first position based on the second position. The controller may be locally integrated within the transport system, remotely located or in the cloud or in some combination thereof. The controller may be configured to analyze the accelerometer data regardless of its location. Depending on the particular situation, this part of the analysis may be to identify the point where the signal rises above the threshold, or it may identify the point where the signal falls below the threshold. The analysis may require identification of the threshold being crossed in a particular direction (e.g., from below to above or from above to below). The threshold may be a positive or negative value, depending on the expected acceleration direction. It will be appreciated that when identifying a threshold crossing in a set of discrete data points, there will be two adjacent data points, one above the threshold and one below the threshold. Any of these data points may be identified as a second position. In some examples, the first position may be identified as the second position (e.g., in the case where the threshold is very close to zero, it may be assumed that crossing the threshold is equivalent to stopping). In other examples, the first location may be determined as a fixed distance (eg, a fixed number of samples) away from the second location, such as to account for additional expected movement of the transport device between a threshold crossing and a stationary state.

[0022] In some examples, the controller is arranged to analyze the accelerometer data to find a third position within the accelerometer data, the third position being the position where the accelerometer data reaches a maximum or minimum value, and wherein the controller is arranged to determine the first position based on the third position. In many cases, the acceleration profile of the transport device will reach a peak acceleration shortly after leaving the fixed position and just before stopping again. In such cases, depending on the sign (direction) of the acceleration, there will be a peak (maximum) in the acceleration or a valley (minimum) in the acceleration. If this peak or valley occurs at a well-defined point in the acceleration profile, it can be used to formulate an accurate start or stop time for the transport device if the peak or valley can be accurately identified. This may involve identifying a turning point, i.e., a peak in the data set, rather than just a high or low point in the data set. In other examples, the identification of the maximum or minimum may be an intermediate step, followed by other analysis steps. In such cases, it may not be necessary to identify the peak, but a simple maximum or minimum in the acceleration data may be sufficient to identify. For example, in some examples, it may be desirable to find certain data features that appear before or after the maximum or minimum. In some examples, it may be useful to identify a crossing of a threshold on a particular side of a maximum or minimum number, such as a point where the data crosses the threshold before reaching the maximum (or minimum) number or a point where the data crosses the threshold after reaching the maximum (or minimum) number. Thus, the above method of determining a second position within the accelerometer data may be limited to data having an identified third position (before or after). back)In some examples, the controller is arranged to determine the second position as a position closest to the third position and on a selected side of the third position at which the accelerometer data crosses a threshold.

[0023] Four specific situations can be highlighted here, depending on whether the transport device starts or stops moving and whether it is traveling upwards or downwards.

[0024] First, in the case where the transport device is initially stationary and begins to move upward (positive acceleration), there will be a positive peak acceleration shortly after the start of the movement with the magnitude of the acceleration then decreasing (becoming a less positive value). The third position will be identified as the position of maximum acceleration, and / or the second position may be identified as the position where the acceleration rises above the positive threshold. In the case where both the second and third positions are identified in the analysis, the second position may be identified as the position where the acceleration crosses the positive threshold before reaching the third position. The first position may be determined as the second position or a fixed distance from the second position.

[0025] Second, in the case where the transport device is initially stationary and begins to move downward (negative acceleration), there will be a negative peak acceleration shortly after the start of the movement with the magnitude of the acceleration subsequently decreasing (becoming less negative). The third position will be identified as the position of minimum acceleration, and / or the second position may be identified as the position where the acceleration drops below the negative threshold. In the case where both the second and third positions are identified in the analysis, the second position may be identified as the position where the acceleration crosses the negative threshold before reaching the third position. The first position may be determined as the second position or a fixed distance from the second position.

[0026] Third, in the case where the conveying device initially moves upward and then stops (negative acceleration), the magnitude of the acceleration will initially increase (become more negative) before reaching a negative peak acceleration shortly before the stop of movement. The third position will be identified as the position of minimum acceleration, and / or the second position may be identified as the position where the acceleration rises above the negative threshold. In the case where both the second and third positions are identified in the analysis, the second position may be identified as the position where the acceleration crosses the negative threshold after reaching the third position. The first position may be determined as the second position or a fixed distance from the second position.

[0027] Fourth, in the case where the conveyor initially moves downward and then stops (positive acceleration), the magnitude of the acceleration will initially increase (become more positive) before reaching a positive peak acceleration shortly before the cessation of movement. The third position will be identified as the position of maximum acceleration, and / or the second position may be identified as the position where the acceleration drops below the positive threshold. In the case where both the second and third positions are identified in the analysis, the second position may be identified as the position where the acceleration crosses the positive threshold after reaching the third position. The first position may be determined as the second position or a fixed distance from the second position.

[0028] Having established the location within the accelerometer data at which the start or stop occurs, the monitoring system can use that information to determine how to process other sensor data (including the accelerometer data). It may be noted that where a low pass filter is used to identify the first, second and / or third locations, this filtered data need not be used in subsequent processing. Instead, the raw accelerometer data may be used. As described above, the processing may be different at different times relative to the start and / or stop. For example, the door closing movement of an elevator car occurs before the start of movement of the car, and the door opening movement is completely after the stop of movement of the car or may have an overlap with the car movement (in the case of an advanced door opening system).

[0029] In some examples, the controller is arranged to associate a motion state of the transport device with the accelerometer data, the motion state being an indication of whether the transport device is in motion or stationary. Associating the motion state with the data may involve storing the motion state in association with each acceleration data value, i.e., forming a data set in which each time entry (sample entry) includes an acceleration data value and a motion state value. Other sensor data may also be included so that each time entry (sample entry) includes an array of several data values. The motion state may be a single bit (e.g., if motion is considered a binary variable; e.g., 'in motion' = '0', 'stationary' = '1'), or it may be a multi-bit value, allowing more states to be defined. In some examples, the motion state may be associated with the accelerometer data by processing the accelerometer data with a fixed time delay (e.g., for health analysis). The fixed time delay is greater than the expected time to determine that a change in motion (start or stop) has occurred. When determining a start or stop, an additional time can be calculated, which is the time difference between the identified start / stop time and the fixed time delay. In other words, the additional time is the amount of time that needs to pass until the determined start stop time coincides with the fixed time delay. At this point, the motion state can be set according to the new state and associated with all (delayed) data processing from that point. For example, in the process for determining the start of a transport device, the motion state associated with the delayed data processing will initially be 'stationary'. If the start of a transport device is determined (through the processing of pressure sensor data and accelerometer data as described above) to have occurred 3 seconds ago, and the fixed delay of the processing is 5 seconds, then an additional time of 2 seconds is required until the motion state associated with the delayed data processing changes to 'in motion'.

[0030] As described above, once the start or stop of the conveying device has been determined, this can be used to determine how to process the buffered accelerometer data. In some examples, the controller is arranged to segregate the accelerometer data into two or more groups based on the first position. In a simple example, the first position can be divided into a group of data before the first position and another group of data above or after the first position. One group can be associated with the conveying device being in motion, and the other group can be associated with the conveying device being stationary. In another example, the accelerometer can be divided into three groups, wherein the first group is defined as a fixed period ending at the first position, the second group is defined as the data before the first group, and the third group is defined as the data after the first group. Such grouping can be used, for example, in an elevator system with advanced door opening, wherein the first position corresponds to an elevator stop. The first group (having a fixed length and terminating at the determined stop) can be associated with the overlap of door motion and car motion. The second group (before the first group) can be associated only with car motion, and the third group (after the first group) can be associated only with door motion.

[0031] Different groups of data may be processed for many different reasons, but one reason is to determine the health of a system or system component. Indicators of health may include the number of times a component (e.g., a door) has been operated, noise or vibration indicating wear, time taken to complete an operation, etc. Accordingly, in some examples, the controller is arranged to process accelerometer data to analyze the health of a transport system, wherein the processing is performed with a fixed time delay, and wherein the controller is arranged to change the type of health analysis when a first position in the accelerometer data corresponds to the fixed time delay. As described above, a change in motion may indicate that certain sensor data (e.g., vibration data from an accelerometer or sound data from a microphone) is generated from a different source. For example, vibrations originate from door operation when the elevator car is stationary, but are generated from interaction with a drive and / or hoistway components (e.g., guide rails) when the car is in motion. Thus, in some examples, the transport system is an elevator system, and the controller is arranged to change the type of health analysis from an elevator door analysis to an elevator car analysis or from an elevator car analysis to an elevator door analysis.

[0032] In some examples, the transport system is an elevator system, and the transport device is an elevator car, wherein the elevator system implements an advance door opening system, and wherein when the controller determines the stop of the elevator car, the controller is arranged to determine the first position in the accelerometer data based on the advance door opening adjustment. In some examples in which the advance door opening system is implemented, there is an overlap of the time between the elevator car door opening and the elevator car being in motion, so that the door begins to open before the elevator car has completely stopped. Therefore, the advance door opening adjustment can be selected to move the first position to an earlier position to account for at least some of the overlap of the time in which the elevator car and the elevator car door are both in motion. This can be used to improve the analysis of the accelerometer data acquired during the overlap period, thereby providing a better separation of pure door car motion from pure door motion, and / or providing a better analysis of the overlap period. The advance door opening adjustment amount can be any suitable amount and can be determined based on factors such as the length of the advance door opening overlap period and the sampling rate. It can be determined by experimentation and / or analysis to give the best performance of the algorithm.

[0033] The monitoring system may be connected to any power source. However, the requirement to connect to the main power source makes it more difficult to install the system. Therefore, it would be helpful if the monitoring system could operate independently and could operate with a separate power source. In some examples, the monitoring system is powered by a battery or an energy harvesting system. The energy harvesting system may, for example, include an inductive charging system, or it may include a system based on heat, power, or wind. In some examples, the monitoring system is not connected to the main power source. With a battery or energy harvesting powered system, low power operation becomes important, and therefore intensive processing volume, sensor sampling rate, and wireless transmission strength become important factors in achieving a suitably long operational life between services.

[0034] In some examples, the monitoring system is independent of the transport system. This again facilitates installation because no communication connection to the existing system controller is required. Thus, health monitoring can be achieved from a separate system and add a layer of safety on top of the fault detection and monitoring system within the transport system itself.

[0035] The sampling rates of the accelerometer and the pressure sensor may be the same, or the pressure sensor may be sampled at a higher rate than the accelerometer. However, the pressure sensor provides less accurate data (e.g., plus or minus half a meter) and is expected to detect large-scale movement in a robust manner. Therefore, it is acceptable to sample it at a lower rate. The accelerometer is capable of detecting very small accelerations (e.g., about milli-g or even micro-g) (e.g., those caused by vibration) and can be sampled at a higher rate to obtain better resolution data. Therefore, in some examples, the sampling rate of the accelerometer is greater than the sampling rate of the pressure sensor. In some examples, the sampling rate of the accelerometer is at least twice, at least three times, at least five times, or even at least ten times that of the pressure sensor. In some examples, the sampling rate may be at least 20 times, at least 50 times, or even at least 100 times that of the pressure sensor. In some examples, the pressure sensor may be sampled at about 1 sample per second, and the accelerometer may be sampled at about 12 samples per second.

[0036] According to a second aspect of the present disclosure, there is provided a method for monitoring a conveying system, comprising:

[0037] Acquiring accelerometer data by sampling an accelerometer on a transport device;

[0038] storing accelerometer data in a buffer;

[0039] Acquiring pressure sensor data by sampling a pressure sensor on a conveying device;

[0040] determining from the pressure sensor data that starting or stopping of the conveyor device has occurred; and

[0041] In the determining, the accelerometer data is analyzed to determine a first location within the accelerometer data, wherein the first location is a location where a start or stop of the transport device occurs.

[0042] It will be appreciated that all of the optional or example features described above with respect to the monitoring system are also optionally applicable to this method of monitoring a conveyor system. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a schematic diagram of an elevator system according to an example of the present disclosure;

[0044] FIG. 2 is a diagram for use according to an example of the present disclosure Figure 1 Schematic diagram of a sensor system for an elevator system;

[0045] Figure 3 is used according to the example of the present disclosure Figure 1 and a schematic diagram of the location of a sensor system of the elevator system of FIG. 2 ;

[0046] Figure 4 is a schematic diagram of a sensing unit according to an example of the present disclosure;

[0047] Figure 5a and Figure 5b is a flow chart illustrating operations performed in a motion change detection process according to an example of the present disclosure;

[0048] Figure 6 is a flow chart illustrating operations performed according to an initial motion detection process according to an example of the present disclosure;

[0049] Figure 7 is a flowchart illustrating operations performed at the end of a motion detection process according to an example of the present disclosure; and

[0050] Figures 8a-8d Figure 1 shows acceleration data illustrating an acceleration distribution of an elevator car according to an example of the present disclosure. picture surface and the manner in which acceleration data is stored to a buffer during the initial motion detection process. DETAILED DESCRIPTION

[0051] Figure 11 is a perspective view of an elevator system 101 including an elevator car 103, a counterweight 105, a tension member 107, a guide rail 109, a machine 111, a position reference system 113, and a controller 115. The elevator car 103 and the counterweight 105 are interconnected by the tension member 107. The tension member 107 may include or be configured as, for example, a rope, a steel cable, and / or a coated steel belt. The counterweight 105 is configured to balance the load of the elevator car 103 and to facilitate movement of the elevator car 103 within the elevator shaft 117 and along the guide rail 109 relative to the counterweight 105 simultaneously and in opposite directions.

[0052] Tension member 107 engages machine 111, which is part of the overhead structure of elevator system 101. Machine 111 is configured to control movement between elevator car 103 and counterweight 105. Position reference system 113 can be mounted on a fixed portion of the top of elevator shaft 117 (e.g., on a support or rail), and can be configured to provide a position signal related to the position of elevator car 103 within elevator shaft 117. In other embodiments, position reference system 113 can be mounted directly to the moving components of machine 111, or can be located in other locations and / or configurations as known in the art. Position reference system 113 can be any device or mechanism for monitoring the position of an elevator car and / or counterweight, as known in the art. For example, without limitation, position reference system 113 can be an encoder, sensor, or other system, and can include rate sensing, absolute position sensing, etc., as will be appreciated by those skilled in the art.

[0053] As shown, the controller 115 is located in a controller room 121 of the elevator shaft 117 and is configured to control the operation of the elevator system 101 and, in particular, the elevator car 103. For example, the controller 115 may provide drive signals to the machine 111 to control the acceleration, deceleration, leveling, stopping, etc. of the elevator car 103. The controller 115 may also be configured to receive position signals from the position reference system 113 or any other desired position reference device. When moving up or down along the guide rails 109 in the elevator shaft 117, the elevator car 103 may stop at one or more landings 125 as controlled by the controller 115. Although shown in the controller room 121, those skilled in the art will appreciate that the controller 115 can be located and / or configured in other locations or positions within the elevator system 101. In one embodiment, the controller may be located remotely or in the cloud.

[0054] The machine 111 may include a motor or similar drive mechanism. According to an embodiment of the present disclosure, the machine 111 is configured to include an electric drive motor. The power source for the motor may be any power source (including the electrical grid), which (in combination with other components) is supplied to the motor. The machine 111 may include a traction sheave that imparts force to the tension member 107 to move the elevator car 103 within the elevator shaft 117.

[0055] Although shown and described using a roping system including tension members 107, elevator systems that use other methods and mechanisms for moving an elevator car within an elevator shaft may employ embodiments of the present disclosure. For example, embodiments may be used in ropeless elevator systems that use linear motors or pressure wheel propulsion to move the elevator car. Embodiments may also be used in ropeless elevator systems that use hydraulic lift to move the elevator car. Figure 1 These are non-limiting examples presented for illustrative and explanatory purposes only.

[0056] In other embodiments, the system includes a transport system that moves passengers between floors and / or along a single floor. Such transport systems may include escalators, people movers, etc. Accordingly, the embodiments described herein are not limited to systems such as Figure 1 In one example, the embodiments disclosed herein may be applicable to a transport system (such as elevator system 101) and a transport device of the transport system (such as elevator car 103 of elevator system 101). In another example, the embodiments disclosed herein may be applicable to a transport system (such as an escalator system) and a transport device of the transport system (such as a moving step of an escalator system).

[0057] Continue to refer to Figure 1 2, a view of a sensor system 200 including a sensing device 210 is illustrated in accordance with an embodiment of the present disclosure. The sensing device 210 is configured to detect sensor data 202 of the elevator car 103 and transmit the sensor data 202 to a remote device 280. The sensor data 202 may include, but is not limited to, pressure data 314, a vibration signature (i.e., vibrations over a period of time) or acceleration 312 and derivatives or integrals of the acceleration 312 of the elevator car 103, such as, for example, distance, velocity, jerk, jounce, snap, etc. The sensor data 202 may also include light, sound, humidity, and temperature or any other desired data parameter. The pressure data 314 may include the atmospheric air pressure within the elevator shaft 117. It should be appreciated that, although specific systems are defined separately in the schematic block diagram, each or any of the systems may be combined or separated in other ways via hardware and / or software. For example, the sensing device 210 may be a single sensor, or may be a plurality of independent sensors that are interconnected.

[0058] In an embodiment, the sensing device 210 is configured to transmit the sensor data 202 to the controller 115 of the elevator system 101 for processing, the sensor data 202 being raw and unprocessed. In another embodiment, the sensing device 210 is configured to process the sensor data 202 by a processing method (such as, for example, edge processing) before transmitting the sensor data 202 to the controller 115. In another embodiment, the sensing device 210 is configured to transmit the sensor data 202 to the remote system 280 for processing, the sensor data 202 being raw and unprocessed. In yet another embodiment, the sensing device 210 is configured to process the sensor data 202 by a processing method (such as, for example, edge processing) before transmitting the sensor data 202 to the remote device 280.

[0059] Processing of the sensor data 202 may reveal data such as, for example, number of elevator door openings / closings, elevator door times, vibrations, vibration signatures, number of elevator rides, elevator ride performance, elevator flight time, possible car positions (e.g., altitude, floor number), re-leveling events, falls back, elevator car 103 x, y acceleration at a certain position: (i.e., track topology), elevator car 103 x, y vibration signature at a certain position: (i.e., track topology), door performance at floor number, nudging events, vandalism events, emergency stops, etc.

[0060] Remote device 280 may be a computing device, such as, for example, a desktop, cloud-based computer, and / or a cloud-based artificial intelligence (AI) computing system. Remote device 280 may also be a computing device typically carried by a person, such as, for example, a smart phone, a PDA, a smart watch, a tablet, a laptop, etc. Remote device 280 may also be two separate devices that are synchronized together, such as, for example, a cellular phone and a desktop computer synchronized via an Internet connection.

[0061] The remote device 280 may be an electronic controller including a processor 282 and associated memory 284 including computer executable instructions that, when executed by the processor 282, cause the processor 282 to perform various operations. The processor 282 may be, but is not limited to, a single processor or a multi-processor system of any of a variety of possible architectures, including field programmable gate arrays (FPGAs), central processing units (CPUs), application specific integrated circuits (ASICs), digital signal processors (DSPs), or graphics processing unit (GPU) hardware (either homogeneous or heterogeneous arrangements). The memory 284 may be, but is not limited to, random access memory (RAM), read-only memory (ROM), or other electronic, optical, magnetic, or any other computer-readable medium.

[0062] The sensing device 210 may be configured to transmit sensor data 202 to the controller 115 or the remote device 280 via a short-range wireless protocol 203 and / or a long-range wireless protocol 204. The short-range wireless protocol 203 may include, but is not limited to, Bluetooth, Wi-Fi, HaLow (801.11ah), zWave, ZigBee, or wireless M-Bus. Using the short-range wireless protocol 203, the sensing device 210 is configured to transmit the sensor data 202 directly to the controller 115 or to the local gateway device 240, and the local gateway device 240 is configured to transmit the sensor data 202 to the remote device 280 or to the controller 115 through a network 250. The network 250 may be a computing network, such as, for example, a cloud computing network, a cellular network, or any other computing network known to those skilled in the art. Using the long-range wireless protocol 204, the sensing device 210 may be configured to transmit the sensor data 202 to the remote device 280 through the network 250. The long-range wireless protocol 204 may include, but is not limited to, cellular, satellite, LTE (NB-IoT, CAT M1), LoRa, Satellite, Ingenu, or SigFox.

[0063] The sensing device 210 may be configured to detect sensor data 202 including accelerations in any number of directions. In an embodiment, the sensing device may detect sensor data 202 including accelerations 312 along three axes (X, Y, and Z), as shown in FIG. 2 . The X-axis may be perpendicular to the door 104 of the elevator car 103, as shown in FIG. 2 . The Y-axis may be parallel to the door 104 of the elevator car 103, as shown in FIG. 2 . The Z-axis may be vertically aligned parallel to the elevator shaft 117 and gravity, as shown in FIG. 2 . The acceleration data 312 may exhibit vibration signatures generated along the X-axis, the Y-axis, and the Z-axis.

[0064] Figure 3 1 shows a possible installation location of a sensing device 210 within an elevator system 101. The sensing device 210 may include a magnet (not shown) for removably attaching to the elevator car 103. Figure 3 In the illustrated embodiment shown in , the sensing device 210 can be installed on the door hook 104a and / or the door 104 of the elevator system 101. It is understood that the sensing device 210 can also be installed in other locations besides the door hook 104a and the door 104 of the elevator system 101. It is also understood that multiple sensing devices 210 can be installed in Figure 3104, and the embodiments disclosed herein may include one or more sensing devices 210. In another embodiment, the sensing device 210 may be attached to the lintel 104e of the door 104 of the elevator car 103. In another embodiment, the sensing device 210 may be located on the lintel 104e near the top 104f of the elevator car 103. In another embodiment, the sensing device 210 is mounted at other locations on the elevator car 103, such as, for example, directly on the door 104.

[0065] like Figure 3 As shown in FIG. , the sensing device 201 may be located in a selected area 106 on the elevator car 103, such as Figure 3 . The door 104 is operably connected to the door lintel 104e by a door hook 104a, which is positioned close to the top 104b of the door 104. The door hook 104a includes a guide wheel 104c, which allows the door 104 to slide open and close along the guide rail 104d on the door lintel 104e. Advantageously, the door hook 104a is an easy to access area for attaching the sensing device 210, because the door hook 104a is accessible when the elevator car 103 is at the landing 125 and the elevator door 104 is open. Therefore, the installation of the sensing device 210 is possible without taking special measures to obtain control of the elevator car 103. For example, the additional safety of an emergency door stop to keep the elevator door 104 open is not necessary, because it is the normal operating mode for the door 104 to be open at the landing 125. The door hook 104a also provides ample clearance for the sensing device 210 during operation of the elevator car 103, such as, for example, the opening and closing of the door 104. Due to the mounting location of the sensing device 210 on the door hook 104a, the sensing device 210 can detect the opening and closing motion (i.e., acceleration) of the door 104 of the elevator car 103 and the door at the landing 125. In addition, mounting the sensing device 210 on the hook 104a allows for the recording of the ride quality of the elevator car 103.

[0066] Figure 4 More detailed illustration Figure 2 and Figure 3312. The example of the sensing device 210 of the present invention is shown in FIG. The sensing device includes a controller 212, a plurality of sensors 217 in communication with the controller 212, a communication module 220 in communication with the controller 212, and a power source 222 electrically connected to the controller 212. The plurality of sensors 217 include an inertial measurement unit (IMU) 218 ​​and a pressure sensor 228. The IMU 218 includes three accelerometers 229 and is configured to detect the acceleration of the elevator car 103 and / or the elevator car door 104, and to generate acceleration data 312. The pressure sensor 228 (the pressure sensor 228 may be, for example, a pressure altimeter or a barometric altimeter) is configured to detect the atmospheric air pressure within the elevator shaft 117 and to generate pressure data 314. Both the IMU 218 and the pressure sensor 228 communicate with the controller 212 of the sensing device 210. In some examples, the plurality of sensors 217 may also include additional sensors, such as light sensors, microphones, humidity sensors, and temperature sensors.

[0067] The power source 222 of the sensing device 210 is configured to store electrical power and supply it to the sensing device 210. The power source 222 may include an energy storage system, such as a battery or a capacitor, or other suitable energy storage system known in the art.

[0068] The communication module 220 is configured to allow the controller 212 of the sensing apparatus 210 to communicate with the remote device 280 and / or the controller 115 via at least one of the short-range wireless protocol 203 and the long-range wireless protocol 204 as described above.

[0069] The controller 212 of the sensing device 210 includes a processor 214 and a memory 216 including computer executable instructions that, when executed by the processor 214, cause the processor 214 to perform various operations, such as processing the sensor data 202 collected by the IMU 218 and the pressure sensor 228 to determine information related to the movement of the elevator car 103. The sensing device 210 also includes a buffer 227 that is configured to store a preset number of data entries.

[0070] Figure 2 and Figure 3The system shown in can be used to monitor the elevator system 101. As previously described, the sensor data 202 is measured in a raw, unprocessed form, and the processing of the sensor data 202 can reveal data related to the elevator system 101. For example, the processing of the acceleration data 312 can allow a fault in the elevator system 101 to be identified. However, in order for the correct processing method to be applied, it is necessary to know whether the acceleration data 312 being processed relates to a stationary elevator car 103 or an elevator car 103 in motion and the direction of the motion of the elevator car 103. This is required in order to separate the acceleration signal caused by the motion of the elevator car 103 itself from the acceleration signal caused by, for example, the movement of the door 104 of the elevator car 103.

[0071] In some examples, to allow for proper processing of acceleration data 312, it is convenient to set a flag indicating the state of motion of elevator car 103, and process acceleration data 312 in accordance with the flag. Accurate determination of the state of motion of elevator car 103 is therefore useful.

[0072] The start and stop of elevator movement (i.e., the change of state between 'in motion' and 'stationary') provide good demarcation points for separating data related to door operation from data related to car movement. However, the start and stop can also be used in elevator systems that employ "advanced door opening" techniques, where there is an overlap in time between the elevator car door opening and the elevator car being in motion (i.e., the door begins to open before the car comes to a complete stop). The start of elevator car movement is still typically a clear separator between the end of the door closing operation and the beginning of elevator car movement. The stop of elevator car movement can be used in conjunction with a known overlap window (e.g., a window of predetermined length) to separate pure door car movement from pure door movement. It will be appreciated that similar overlap windows will also be used at the start of elevator movement for other reasons, such as to account for other sources of vibration, such as advanced brake lift operations, which may overlap with door movement and / or car movement.

[0073] The process for monitoring the movement of a transport device (e.g., an elevator car) may be improved by using the pressure data 314 to detect that a change in the movement of the transport device has occurred, and then analyzing the buffer acceleration data 312 only once a change in movement is detected in order to more accurately determine when the change in the movement of the transport device occurred.

[0074] Now refer to Figure 5a A process for monitoring movement of a transport device in a transport system according to an example of the present disclosure is described.

[0075] In the examples described herein, the transport system is an elevator system 101 and the transport equipment is an elevator car 103. However, it will be appreciated that the same process is equally applicable to systems including escalator systems and moving walkways. one Serial Conveyor System. The process illustrated in FIG. 5 may be performed by one or more of sensing apparatus 210, controller 115, and remote device 280 using data from sensing apparatus 210, as will be described below.

[0076] At block 500, the acceleration of the elevator car 103 is measured using the IMU 218, and the acceleration data 312 is stored in the memory 216 of the sensing device 210. The acceleration of the elevator car 103 is measured at a specific sampling frequency, such as 12 samples per second. In one example, any desired sampling frequency may be used. The acceleration data 312 stored in the memory 216 of the sensing device 210 is at least temporarily saved in a buffer 227. The buffer 227 has a size of at least n+1, that is, it is configured to store at least n+1 data values ​​corresponding to the n+1 most recent acceleration measurements. Each acceleration measurement stored in the buffer 227 has an associated index between 0 and n, where the most recent entry in the buffer 227 has an index of 0, and the oldest entry in the buffer 227 has an index of n. As each new acceleration measurement is saved to the buffer 227, the index of each of the previous entries is increased by one, and the entry with index n is removed from the buffer 227. Thus, a series of the n+1 most recent acceleration measurements are temporarily stored in the buffer 227, and the series is updated with each new acceleration measurement saved to the buffer 227. The size of the buffer 227 may be selected based on characteristics of the elevator system 101, for example, based on the expected acceleration behavior of the elevator car 103 and / or based on the expected update frequency of the acceleration measurements from the IMU 218. As an example, the buffer 227 may be implemented as a shift register, or it may be implemented as a sliding window within a larger area of ​​memory.

[0077] At block 502, a change in the height of the elevator car 103 is determined using the pressure sensor 228 of the sensor device 210. The pressure sensor 228 measures the atmospheric air pressure near the elevator car 103 at a sampling rate (e.g., 1 sample per second), and determines whether the height of the elevator car 103 has changed based on the measured pressure. The sampling rate at which pressure measurements are obtained may be significantly lower than the sampling rate at which acceleration measurements are obtained. The determination of the change in the height of the elevator car 103 may be made, for example, by comparing the measured air pressure with a previously measured air pressure value stored in the memory 216 of the sensing device 210 and calculating the difference. The difference in air pressure may be compared to a threshold, and if this threshold is exceeded, it may be determined that the height of the elevator car 103 has changed, corresponding to a change in the motion of the elevator car 103. This change in height over time need not be from adjacent pressure samples, but may span several samples. For example, a change of 1.5 m in the space of 4 seconds may be considered to robustly identify that a change in motion has occurred. The process then proceeds to block 504.

[0078] At block 504 , the acceleration measurements stored in buffer 227 are analyzed to determine a location (or index value i) within the accelerometer data that corresponds to a change in the motion of elevator car 103 (ie, a start or stop).

[0079] This analysis at step 504 may be accomplished by determining a second position within the accelerometer data where the acceleration crosses a threshold. The threshold may be selected to be a value that is small enough to indicate that the elevator car 103 has just begun to move or is about to stop moving, but large enough to avoid being triggered by sensor noise. The analysis in step 504 may also involve determining a third position within the accelerometer data where a maximum or minimum value of the accelerometer data is reached. This third position may be determined prior to determining the second position. In such cases, additional constraints may be imposed on the determination of the second position: such as crossing the threshold on a particular side of (i.e., before or after) a maximum or minimum number. For example, it may be desirable to determine a point where the acceleration threshold is crossed before the maximum value is reached (and thereby exclude from processing any possible thresholds that are crossed after the maximum value).

[0080] The processing of the accelerometer data depends on the type of change in motion being determined (eg, whether the change in motion corresponds to a start or stop of elevator car 103 ), and also on whether elevator car 103 is traveling up or down hoistway 117 .

[0081] Since the accelerometer data corresponding to the start and stop of the elevator car 103 is low frequency, a very steep, ultra-low pass filter (i.e., a filter with a low cutoff frequency and steep frequency transitions) can first be applied to the acceleration measurements stored in the buffer 227. The filter ideally has a minimum or linear phase delay. This filter removes high frequency components from noise and other vibrations, thereby simplifying the processing of the acceleration measurements stored in the buffer 227.

[0082] Figure 5b and Figure 5a Similarly, but additional steps for additional analysis of accelerometer data according to one example are shown. After identifying a start or stop of a transport device (e.g., elevator car 103) in step 504, the process calculates the difference between the identified start or stop (i.e., the first position) and the end of the buffer (representing the earliest data element). This difference (Δi) represents the number of new samples of accelerometer data that must be acquired before the first position (start or stop) reaches the end of the buffer. When this occurs, it is known that a fixed time (corresponding to the length of the buffer 227) has passed since the start or stop occurred. Older accelerometer data (i.e., older than the length of the buffer) can then be processed with certainty about the motion state of the elevator car 103 at that time. Therefore, in step 508, the system waits for Δi more accelerometer samples so that the start or stop is at the end of the buffer 227, and in step 510, the system updates the motion state flag, which indicates whether the transport device is "in motion" or "stationary."

[0083] As Figure 5b , in which case the elevator car 103 begins to leave a stationary position, the processing of steps 500, 502 and 504 will begin with the motion state flag being set to "stationary", and will identify the index i at which the start occurs. The system then takes other accelerometer samples, loads them into one end of the buffer, and moves all other data along the buffer (but without making changes to the motion state flag) until the start has reached index n in the buffer. Only at this point is the motion state flag updated from "stationary" to "in motion". Up to this point, data older than the buffer length is known to correspond to a stationary state as indicated by the motion state flag. The update of the flag state indicates that this is no longer the case, and therefore data older than the buffer length can no longer be considered pure "stationary" data. This allows simple processing of the accelerometer data using a fixed processing delay. Although it is convenient to have the processing delay correspond to the length of the buffer 227 as described herein, it will be appreciated that this need not be the case, and that a longer or shorter fixed processing delay can be used, as long as it is long enough to ensure that the start or stop reliably occurs before the fixed processing delay.

[0084] The processing of the accelerometer data after a fixed processing delay may be used to analyze the health of one or more components of the transport system. For example, if it is determined that the elevator car 103 is in motion after an identified change in motion, the raw (i.e., unfiltered) accelerometer data may be processed to determine the condition of the elevator car 103 and the guide rails within the shaft 117. Similarly, if the elevator car 103 is determined to be stationary, it is likely that any measured acceleration will be caused by the door 104 of the elevator car 103. Therefore, the raw acceleration data obtained when the elevator car 103 is stationary may be processed to determine the condition of the elevator car door 104. Such processed data may be transmitted to the remote device 280 using the short-range wireless protocol 203 and / or the long-range wireless protocol 204 to allow any faults with the elevator system 101 to be identified without, for example, manual inspection of the elevator system 101. Such analysis may also be used by a condition-based maintenance system to predict and schedule maintenance of the system 101.

[0085] Reference Figure 5a and Figure 5b A general process for determining a change in the motion of the elevator car 103 is described and will be referred to in Figure 6 Two specific situations are described with reference to FIG. 8 .

[0086] Figure 6 A process for determining the start of motion of an elevator car 103 in accordance with the present disclosure is shown. In block 600, it is determined that the elevator car 103 is stationary (i.e., the motion state flag indicates that the elevator car 103 is not in motion). In block 602, a change in pressure is determined by using the pressure sensor 228 of the sensor device 210 as previously described. Based on the change in pressure, a change in the height of the elevator car 103 is calculated. If the change in height in a given time period is greater than a threshold value (e.g., 1.5 meters in 4 seconds), the process proceeds to block 604, where a direction of travel is determined, for example, based on the sign of the change in height. Based on the direction of travel, the process proceeds to block 606a or block 606b (if the direction of travel is up or down, respectively). It will be appreciated that calculation of the change in height is not strictly required, but in some embodiments, the measured change in pressure may be compared to a threshold value instead of the change in height.

[0087] If it is determined that the change in altitude is in the vertically upward direction, the process proceeds to block 606a. In block 606a, a low pass filter is applied to the acceleration measurements stored in buffer 227. The index i of the maximum acceleration value is then identified. max To determine the index associated with the start of a movement, the index i stored in buffer 227 having an acceleration value greater than the maximum acceleration value is max The indexed acceleration measurement (i.e., the earlier measurement) is equal to the upward acceleration threshold a 1(e.g. 10 mg) in order to increase the index value. Then the acceleration threshold a is detected. 1 The index i of the first acceleration value up , and index i up -1 is determined as the index associated with the start of motion. The decrement by 1 in this example selects values ​​of acceleration above the threshold, rather than values ​​below the threshold (lower index values ​​represent newer measurements), but in other examples, this decrement may be omitted. In block 608, if the acceleration value stored in buffer 227 is not determined to be below the acceleration threshold a, then the value of acceleration stored in buffer 227 is determined to be below the acceleration threshold a. 1 , it is possible that the start may not have occurred yet due to errors in the pressure readings, etc. However, if the identification index i up -1, it is determined that the elevator car 103 is in motion, and in block 610 based on the identified index i up -1 to identify the location within the accelerometer data where the upward motion begins. Figure 5b In some examples, the index i of the start of the movement of the elevator car 103 is identified. up -1, the system waits until the identified index i up -1 moves to the final position (n) of the buffer 227 and then changes the flag state from 0 to 1 (ie, from "stationary" to "in motion").

[0088] However, if it is determined in step 604 that the change in altitude is in a vertical downward direction, then the process proceeds to block 606b. In block 606b, a low pass filter is applied to the acceleration measurements stored in buffer 227. The index i of the minimum acceleration value is then identified. min To determine the index associated with the start of a movement, the index i stored in buffer 227 having an acceleration value greater than the minimum acceleration value is min The indexed acceleration measurement (i.e., the earlier measurement) is equal to the acceleration threshold a in the downward direction. 1 (e.g. -10 mg) in order to increase the index value. Then the acceleration threshold a is identified. 1 The index i of the first acceleration value down , and index i down -1 is determined as the index associated with the start of motion. The decrement by 1 in this example selects values ​​where the acceleration is above the threshold, rather than below the threshold (lower index values ​​represent newer measurements), but in other examples this decrement may be omitted. In block 608, if the acceleration value is not determined to be above the acceleration threshold a, then the value is decremented by 1. 1 , it is possible that the start may not have occurred yet due to errors in the pressure readings, etc. However, if the identification index i down-1, it is determined that the elevator car 103 is in motion, and in block 610 based on the identified index i as previously described down -1 and the length n of the buffer to identify the position within the accelerometer data where the motion begins. The motion state flag may then be set to indicate that the elevator car 103 is in motion. In some examples, the index i identifying the start of motion of the elevator car 103 down -1, the system waits until the identified index i down -1 moves to the final position (n) of the buffer 227 and then changes the flag state from 0 to 1 (ie, from "stationary" to "in motion").

[0089] Figure 7 A process for determining the end of motion of an elevator car 103 in accordance with the present disclosure is shown. In box 800, it is determined that the elevator car 103 is moving (i.e., the motion state flag indicates that the elevator car 103 is in motion). In box 802, a change in pressure is determined by using the pressure sensor 228 of the sensor device 210 as previously described. Based on the change in pressure, the change in the height of the elevator car 103 is calculated. If the change in height in a given time is less than a threshold value (e.g., 1.5 meters in 4 seconds), the process continues to box 804. In box 804, the direction of travel is checked and used to determine the next step of the process. The direction of travel may be known from earlier processing, or may be determined based on, for example, pressure or acceleration data before other steps are performed.

[0090] If the direction of travel is known to be upward, the process proceeds to block 806a. However, if the direction of travel is known to be downward, the process proceeds to block 806b. As previously described, it will be appreciated that calculation of the change in altitude is not strictly required, but in some embodiments, the change in measured pressure may be compared to a threshold instead of a change in altitude.

[0091] If the known direction of travel of the elevator car 103 is upward, then in block 806a, a low pass filter is applied to the acceleration measurements stored in the buffer 227. The index i of the minimum acceleration value is then identified. min To determine the index associated with the end of the movement, the index i stored in the buffer 227 having an acceleration value less than the minimum acceleration value is min The acceleration measurement indexed by (i.e., the newer measurement) is equal to the downward acceleration threshold a 1 (e.g. -10 mg) in order to reduce the index value. Then the acceleration threshold a is identified. 1 The index i of the first acceleration value * up , and index i * up+2 is determined to be the index associated with the end of the motion. The increment of 2 in this example is to move the identified position forward one position in the measurement history in order to account for the advanced door opening feature. The value of "2" can vary according to the specific implementation and can be established through analysis and optimization to find the best value. In other examples, such as in the absence of an advanced door opening, this increment can be omitted (or can be a decrement instead). In block 808, if the acceleration value is not determined to be above the acceleration threshold a, then the acceleration value is determined to be above the acceleration threshold a. 1 , then it is possible that something has gone wrong in the measurement or processing, and therefore the system immediately returns the motion state to zero (or "stationary") because this is the safest assumption. Therefore, in this situation, the process continues to block 810a and actually determines that the motion of the elevator car 103 ends completely at index 0 (i.e., the most recent measurement corresponding to "now"). However, if the identification index i* up +2, the process proceeds to block 810b. In block 810b, it is determined that the elevator car 103 is stationary, and based on the identified index i * up +2 to identify the position in the accelerometer data where the movement of the elevator car 103 ends. The motion state flag may then be set to indicate that the elevator car 103 is stationary. In some examples, the index i that identifies the stop of the movement of the elevator car 103 * up +2, the system waits until the identified index i * up +2 moves to the final position (n) of the buffer 227, and then changes the motion state flag from 1 to 0 (ie, from "in motion" to "stationary").

[0092] If the known direction of travel of the elevator car 103 is downward, then in block 806b, a low pass filter is applied to the acceleration measurements stored in the buffer 227. The index i of the maximum acceleration value is then identified. max To determine the index associated with the end of the movement, the index i stored in the buffer 227 having an acceleration value less than the maximum acceleration value is max The acceleration measurement indexed by (i.e., the newer measurement) is equal to the upward acceleration threshold a 1 (e.g. 10 mg) in order to reduce the index value. Then the acceleration threshold a is detected. 1 The index i of the first acceleration value * down , and index i * down+2 is determined to be the index associated with the end of the motion. The increment of 2 in this example is to move the identified position forward one position in the measurement history in order to account for the advanced door opening feature. The value of "2" can vary according to the specific implementation and can be established through analysis and optimization to find the best value. In other examples, such as in the absence of an advanced door opening, this increment can be omitted (or can be a decrement instead). At block 808, if the acceleration value is not determined to be below the acceleration threshold a, then the acceleration value is determined to be below the acceleration threshold a. 1 , then it is possible that something has gone wrong in the measurement or processing, and therefore the system immediately returns the motion state to zero (or "stationary") because this is the safest assumption. Therefore, in this situation, the process continues to block 810a and actually determines that the motion of the elevator car 103 ends completely at index 0 (i.e., the most recent measurement corresponding to "now"). However, if the identification index i * down +2, the process proceeds to block 810b. In block 810b, it is determined that the elevator car 103 is stationary, and based on the identified index i * down +2 to identify the position in the accelerometer data where the movement of the elevator car 103 ends. The motion state flag may then be set to indicate that the elevator car 103 is stationary. In some examples, the index i that identifies the stop of the movement of the elevator car 103 * down +2, the system waits until the identified index i * down +2 moves to the final position (n) of the buffer 227, and then changes the motion state flag from 1 to 0 (ie, from "in motion" to "stationary").

[0093] so, Figure 6 and Figure 7 The processes described in the can be used to accurately determine when (or data index) a change in the motion of the elevator car 103 occurs, and to set flags based on the motion of the elevator car 103, without the need for constant processing of accelerometer data. Processing of the acceleration data is performed only when the pressure sensor 228 identifies a change in the position of the elevator car, and these processes allow for significant resource (e.g., power) savings, and allow accurate determination of changes in car motion to be made.

[0094] Figure 8a An example of low pass filtered acceleration values ​​a(t) is shown which are stored in a buffer 227 of length 10 and used as described above with respect to Figure 6It should be understood that the example shown in FIG8 is illustrative only, and the acceleration values ​​and buffer lengths shown are not necessarily representative of those expected to be actually used. For example, in practice, the buffer may be longer, or may have a significantly finer time resolution than that shown. Figure 8a In the example shown, the maximum acceleration value stored in the buffer 227 (represented by the peak 701) can be seen to have the index i max =5. Acceleration threshold a 1 This is shown by the dashed line 703. 1 The first acceleration value of magnitude can therefore be seen to have index i up = 7. The start of the upward movement is then determined as the start at index i up -1=6 has occurred. Based on this determination, the motion state flag can be set to indicate that there is a greater than i up Buffer values ​​with indices less than or equal to i are associated with a stationary elevator car (and thus may be associated with movement of, for example, elevator car door 104), while buffer values ​​with indices less than or equal to i up The buffer values ​​indexed at -1 are associated with the motion of the elevator car 103 itself. This isolation of data is Figure 8b It is shown in Figure 8b The first grouping 705 (earlier than i) of data points identified as belonging to door motion (stationary elevator car 103) is shown. up -1) and a second grouping 706 of data points identified as belonging to the moving elevator car 103 (i up -1 and newer).

[0095] Figure 8c and Figure 8d Two approaches are shown in which a change in the movement of the elevator car 103 has been determined and the associated index value (i up -1) Then, a movement state flag indicating the state of movement of the elevator car 103 is set.

[0096] Figure 8c A first method of setting a flag 708 indicating the state of the motion of the elevator car 103 is shown. Figure 8c In the illustrated method, each accelerometer data value has an associated flag value 708 indicating whether the elevator car 103 was in motion (flag 708 set to 1) or stationary (flag 708 set to 0) at the time of that acceleration value. Such data can be stored and later processed in bulk while retaining precise knowledge of which data points correspond to which motion state.

[0097] Figure 8dA second method of setting a flag indicating the status of the movement of the elevator car 103 is shown, where once a change in the movement of the elevator car 103 is identified as having occurred before a fixed time (thereby allowing delayed processing with a fixed time delay), a flag 710 is set. Figure 8d shows a series of five consecutive snapshots of accelerometer data in time, each snapshot having acquired a new data sample relative to the snapshot above. Figure 8d In the first (upper) set of values ​​shown, buffer 227 can be seen to contain 10 values, corresponding to Figure 8a In addition to the earlier value 707 which is no longer stored in the buffer 227, the end of the buffer 227 (shown by the dashed line 709) is also Figure 8d In Figure 8d In the top row of , the earlier value 707 corresponds to a time when the elevator car 103 is known to be stationary, and therefore at this time, the flag 710 is set to 0. As each new value is saved to the buffer 227 (at position 0 on the right end), the other acceleration measurements are shifted to the left (the index is increased by one), and the oldest value in the buffer 227 (having an index value of i=9 in this example) is removed from the buffer 227. Figure 8d In the example shown, an index value (i up -1). When this value exceeds the last entry in buffer 227 (i.e., an entry with an index greater than n), then flag 710 changes from 0 to 1 to indicate that elevator car 103 was in motion for a fixed time in the past, which corresponds to the length of buffer 227. Figure 8d , this occurs in the last (fifth) row when the value "15" from the original index 6 (in the first row) is shifted to the left of the dashed line 709. The flag 710 then remains set to 1 until it is determined that the elevator car 103 is stationary again, i.e., until the elevator car 103 is stationary as described above. Figure 7 The end of the movement of the elevator car 103 is identified. Figure 8d It can be seen that this processing can be done in real time with only a single bit flag 710, without the need to store the flag in association with the data. The motion state of the earlier data 707 is precisely known, and therefore this data 707 can be processed with a time delay equal to the length of the buffer 227. and And use mark 710 to indicate the change of motion state associated with that data 707. Mark 710 will reliably indicate the recent change with the earlier data point 707. Data Points The motion state of the associated elevator car 103 .

[0098] It will be appreciated by those skilled in the art that the present disclosure has been illustrated by describing one or more specific examples thereof, but that the present disclosure is not limited to these examples; many variations and modifications are possible within the scope of the appended claims.

Claims

1. A monitoring system for a conveying system, comprising: A pressure sensor mounted on the conveying device; an accelerometer mounted on the transport device; as well as A controller arranged to: acquiring accelerometer data by sampling the accelerometer; storing the accelerometer data in a buffer; acquiring pressure sensor data by sampling the pressure sensor; determining from the pressure sensor data that a start or stop of the conveying device has occurred; as well as Only upon determining that a start or stop of the transport device has occurred, the accelerometer data is analyzed to determine a first position within the accelerometer data, wherein the first position is the position where the start or stop of the transport device occurred.

2. The monitoring system according to claim 1, wherein: The controller is arranged to determine that starting or stopping of the conveying device has occurred based on detecting a change in the pressure data of at least a threshold amount within a predetermined time period.

3. The monitoring system of claim 1, wherein: The controller is arranged to analyse a recent time window of the accelerometer data.

4. The monitoring system according to claim 1, wherein: The controller is arranged to filter the accelerometer data using a low pass filter.

5. The monitoring system according to any one of claims 1 to 4, wherein: The controller is arranged to analyse the accelerometer data to find a second position within the accelerometer data, the second position being a position where the accelerometer data crosses a threshold, and wherein the controller is arranged to determine the first position based on the second position.

6. The monitoring system according to any one of claims 1 to 4, wherein: The controller is arranged to analyse the accelerometer data to find a third position within the accelerometer data, the third position being a position where the accelerometer data reaches a maximum or minimum value, and wherein the controller is arranged to determine the first position based on the third position.

7. The monitoring system according to any one of claims 1 to 4, wherein: The controller is arranged to associate a motion state of the transport device with the accelerometer data, the motion state being an indication of whether the transport device is in motion or at rest.

8. The monitoring system according to any one of claims 1 to 4, wherein: The controller is arranged to segregate the accelerometer data into two or more groups based on the first position.

9. The monitoring system according to any one of claims 1 to 4, wherein: The controller is arranged to process the accelerometer data to analyse the health of the transport system, wherein the processing is performed with a fixed time delay, and wherein the controller is arranged to change the type of health analysis when the first position in the accelerometer data corresponds to the fixed time delay.

10. The monitoring system of claim 9, wherein: The transport system is an elevator system, and wherein the controller is arranged to change the type of health analysis from an elevator door analysis to an elevator car analysis or from an elevator car analysis to an elevator door analysis.

11. The monitoring system according to any one of claims 1 to 4, wherein: The transport system is an elevator system and the transport equipment is an elevator car, wherein the elevator system implements an advanced door opening system, and wherein when the controller determines a stop of the elevator car, the controller is arranged to determine the first position within the accelerometer data also based on an advanced door opening adjustment.

12. The monitoring system according to any one of claims 1 to 4, wherein: The monitoring system is powered by a battery or an energy harvesting system.

13. The monitoring system according to any one of claims 1 to 4, wherein: The monitoring system is independent of the transport system.

14. The monitoring system according to any one of claims 1 to 4, wherein: The sampling rate of the accelerometer is greater than the sampling rate of the pressure sensor.

15. A method for monitoring a conveyor system, comprising: Acquiring accelerometer data by sampling an accelerometer on a transport device; storing the accelerometer data in a buffer; acquiring pressure sensor data by sampling a pressure sensor on the transport device; determining from the pressure sensor data that a start or stop of the conveying device has occurred; as well as Only upon determining that a start or stop of the transport device has occurred, the accelerometer data is analyzed to determine a first position within the accelerometer data, wherein the first position is the position where the start or stop of the transport device occurred.

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