Patent Description:
Ride quality of elevator systems is one of the main metrics of passenger comfort in an elevator car. Currently, ride quality is measured during commissioning and during maintenance. A technician places a portable device on the floor of the elevator car. The portable device takes measurements related to the ride quality. These measurements are readable by the technician to determine the quality of the ride at that time.

<CIT> discloses a system and method of measuring and diagnosing the ride quality of an elevator system including operating a mobile device to acquire ride quality data, operating the mobile device to transmit ride quality data to an external computing device and operating the external computing device to perform ride quality diagnostics.

<CIT> discloses a monitoring unit for monitoring an elevator, comprising at least one sensor unit for detecting at least one variable of the elevator and at least one communication unit for transmitting data to a network.

<CIT> discloses a method for monitoring a conveying system with a monitoring device, in which a signal pattern progression is recorded in relation to a functional unit of the conveying system, and is compared to a reference signal progression stored in a database.

According to an aspect of the present invention, a monitoring system is provided as recited in claim <NUM>.

According to another aspect of the present invention, a monitoring method includes generating, at an elevator system, one or more data streams describing the ride of an elevator system as recited in claim <NUM>.

According to yet another aspect of the present invention, a computer-program product for monitoring an elevator system includes a computer-readable storage medium having program instructions embodied therewith is provided as recited in claim <NUM>.

The one or more data streams generated at the elevator system include vibration data generated by a vibration sensor or audio data captured by a microphone, or both.

In some embodiments, the monitoring system comprises a sensor of trigger events, and the vibration sensor is configured to be activated upon detection of a trigger event by the sensor of trigger events, and to generate the vibration data responsive to the trigger event.

In some embodiments, the monitoring system comprises a sensor of trigger events, and the microphone is configured to be activated upon detection of a trigger event by the sensor of trigger events, and to captures the audio data responsive to the trigger event.

In some embodiments, local preprocessing is performed, at the elevator system, on the one or more data streams to generate the sensor data.

In some embodiments, the audio data captured by the microphone includes audio during a run of the elevator system as well as audio of a run of a second elevator system.

In some embodiments, calibration is performed. The calibration includes determining one or more transformations between the sensor data and measurements taken by a measurement device.

In some embodiments, the analytics system learns, by machine learning based on historical sensor data, to recognize the ride quality of the elevator system.

In some embodiments, the analytics system automatically performs a remedial action responsive to the ride quality of the elevator system.

Technical effects of embodiments of the present disclosure include remote monitoring of the continuous ride quality of an elevator system, and optionally in real time, without the need for a technician to be present at the elevator system. Thus, an alert can be generated to dispatch a technician if performance of the elevator system is sufficiently degraded. Additionally, the technician can be alerted to likely problems and can therefore arrive prepared to make the expected repairs.

The counterweight <NUM> is configured to balance a load of the elevator car <NUM> and is configured to facilitate movement of the elevator car <NUM> concurrently and in an opposite direction with respect to the counterweight <NUM> within an elevator hoistway <NUM> and along the guide rail <NUM>.

The controller <NUM> is located, as shown, in a controller room <NUM> of the elevator hoistway <NUM> and is configured to control the operation of the elevator system <NUM>, and particularly the elevator car <NUM>. When moving up or down within the elevator hoistway <NUM> along guide rail <NUM>, the elevator car <NUM> may stop at one or more landings <NUM> as controlled by the controller <NUM>.

Although shown and described with a roping system as the tension member <NUM>, elevator systems <NUM> that employ other methods and mechanisms of moving an elevator car within an elevator hoistway <NUM> may employ embodiments of the present disclosure. For example, embodiments may be employed in ropeless elevator systems <NUM> using a linear motor to impart motion to an elevator car <NUM>. An embodiment may also be employed in a ropeless elevator system <NUM> using a hydraulic lift to impart motion to an elevator car <NUM>.

<FIG> is a diagram of a monitoring system <NUM> for monitoring the continuous ride quality of a conveyance system, such as an elevator system <NUM>, according to some embodiments of this disclosure. Although this disclosure describes in detail application of the monitoring system <NUM> to an elevator system <NUM>, it will be understood by one skilled in the art that various embodiments may be applicable to escalators or other conveyance systems.

The monitoring system <NUM> includes one or more of a vibration sensor <NUM> and a microphone <NUM>. In some embodiments, the vibration sensor <NUM> or the microphone <NUM>, or both, are connected to a processing unit <NUM>, which receives measurements from the connected vibration sensor <NUM> or microphone <NUM>, or both. Through a communication device <NUM>, the processing unit <NUM> may be connected to a cloud <NUM>. The processing unit <NUM> may thus transmit sensor data <NUM> to the cloud <NUM>, where an analytics system <NUM> may perform analytics to determine continuous ride quality and thereby monitor continuous ride quality remotely.

Although <FIG> shows the vibration sensor <NUM>, the microphone <NUM>, the processing unit <NUM>, and the communication device <NUM> positioned together, this is for illustrative purposes only. When both the vibration sensor <NUM> and the microphone <NUM> are used, these may be separate devices or may be integrated together into a single detection device. Additionally, each of the processing unit <NUM> and the communication device <NUM> may be a distinct device as well. Further, these various components need not be positioned together in the elevator system <NUM> but, rather, may be distributed throughout the elevator system <NUM>, as will be discussed further below. Thus, although <FIG> illustrates a single device as the vibration sensor <NUM>, the microphone <NUM>, the processing unit <NUM>, and the communication device <NUM>, it will be understood by one skilled in the art that the monitoring system <NUM> may include one or multiple devices for these purposes.

As shown in <FIG>, the vibration sensor <NUM>, the microphone <NUM>, the processing unit <NUM>, and the communication device <NUM> may be positioned above the elevator car <NUM>. However, other positions of the monitoring system <NUM> may also be used. For example, and not by way of limitation, the vibration sensor <NUM> may be built into a wall of the elevator car <NUM> or affixed on a door header of the elevator car <NUM>. For further example, the microphone may be integrated into the elevator car <NUM> as part of an in-car telecommunications systems, which may be useable for additional purposes other than those described herein. The processing unit <NUM> may be positioned so as to enable a connection with each of the vibration sensor <NUM> and the microphone <NUM>, and the communication device <NUM> may be positioned so as to enable a connection with the processing unit <NUM>. Each of the vibration sensor <NUM>, the microphone <NUM>, the processing unit <NUM>, and the communication device <NUM> may be affixed to or integrated with the elevator system <NUM> or may be placed in or on aspects of the elevator system without being affixed.

As discussed above, conventionally, a portable device is used during commissioning and during maintenance to test the ride quality of an elevator system at the time of such commissioning or maintenance. However, the events of commissioning and maintenance are short-term, and thus the testing performed at those times is not sufficient to obtain a full picture of the ride quality. Additionally, because only a single person is typically involved with measuring the ride quality, no variation of passenger volumes is considered with conventional mechanisms. According to some embodiments of this disclosure, however, ride quality can be monitored on a continuous basis in real time. Further, because the vibration sensor <NUM> may have higher fidelity than a conventional device used to measure ride quality, the measurements taken may be more reliable. Further, because further analytics may be performed in the cloud <NUM>, the ride quality can be monitored and analyzed remotely, with various passenger volumes.

In some embodiments of this disclosure, the vibration sensor <NUM> is an accelerometer, such as a three-axis accelerometer. Thus, the vibration sensor <NUM> may detect vibrations in three dimensions. In some embodiments, the vibration sensor <NUM> may detect vibrations in one or two dimensions. In some embodiments, multiple vibration sensors <NUM> may be used. Generally, the vibration sensor <NUM> may output a data stream of vibration data, which includes measurements that describe vibrations detected during an elevator run of the elevator system <NUM>. The vibration sensor <NUM> may be in communication with the processing unit <NUM> and may thus transmit that data stream to the processing unit <NUM>.

In contrast to the conventional portable device, the vibration sensor <NUM> may remain with the elevator system <NUM> regardless of whether a technician is present. Specifically, the vibration sensor <NUM> may stay with the elevator system <NUM> continuously from installation until removal, which may be days, months, or years later. Additionally, the vibration sensor <NUM> may continue to deliver detected measurements to the processing unit <NUM>.

The vibration sensor <NUM> need not detect vibrations all the time. Rather, the vibration sensor <NUM> is in either sleep mode or active mode at a given time, such that the vibration sensor <NUM> measures vibrations during active mode but not during sleep mode. The active mode is triggered responsive to a set of one or more trigger events, where the existence of at least one trigger event causes the vibration sensor <NUM> to switch to active mode. According to the claimed invention, a trigger event is the presence of at least one person inside the elevator car. To this end, for instance, a motion sensor or other device for detecting presence may be in communication with the vibration sensor <NUM>, or a motion sensor or other presence detector may be in communication with the controller <NUM>, which may communicate information as needed to the vibration sensor <NUM>. In this manner, the vibration sensor <NUM> may be switched to active mode when a trigger event occurs. For additional examples, trigger events may include one or more of the following: movement of the elevator car <NUM>, which may be detected by the controller <NUM>; or the elevator doors being closed, which may also be detected by the controller <NUM>.

The vibration sensor <NUM> may return to sleep mode responsive to a set of one or more sleep events, where the existence of at least one of such sleep events may cause the vibration sensor <NUM> to switch into sleep mode. Sleep events may include one or more of the following, for example: passage of a predetermined period of time after the last trigger event occurred; having reached a landing, which may be detected by the controller <NUM>; or the elevator doors being open, which may be detected by the controller <NUM>. Detection of a trigger event or a sleep event may be implemented in various ways, such as connecting a sensor of the trigger events and the sleep events to the processing unit <NUM> or to the controller <NUM>, either of which may activate or deactivate the vibration sensor <NUM> as needed.

The microphone <NUM> captures audio associated with movement of the elevator car <NUM> and, specifically, movement during an elevator run. Generally, this can be useful because a typical elevator ride is relatively quiet without unexpected noises, and the sound of the ride typically falls within an expected range. The microphone <NUM> may be positioned inside the elevator car, on top of the elevator car <NUM>, or elsewhere in a position where the microphone <NUM> is capable of catching sounds emitted by movement of the elevator car <NUM>. The microphone <NUM> may output a data stream of audio data representing the audio captured. The microphone <NUM> may be in communication with the processing unit <NUM> and may thus transmit this data stream to the processing unit <NUM>.

When the microphone <NUM> is positioned on top of the elevator car <NUM>, the audio captured may relate to not only the elevator system <NUM> in which the microphone is positioned, but also to one or more other nearby elevator systems <NUM>. In other words, when positioned over the elevator car <NUM>, the microphone is not isolated from background noise caused by nearby elevator systems <NUM> within the range of the microphone <NUM>, and thus the microphone's output relates to those nearby elevator systems <NUM> as well. For instance, a group of two or more elevator systems <NUM> may be positioned nearby one another, perhaps sharing an elevator bay, and perhaps having connected or nearby elevator shafts. In that case, a microphone <NUM> positioned on top of the elevator car <NUM> of one of such elevator systems <NUM> may pick up audio representing the movements of the other elevator cars <NUM>. This can be advantageous because, in some embodiments, a nearby elevator system <NUM> can be monitored by the monitoring system <NUM> without itself being outfitted with a microphone <NUM>.

The microphone <NUM> need not capture audio all the time. Rather, the microphone <NUM> is in either sleep mode or active mode at a given time, such that the microphone <NUM> captures audio during its active mode but not during its sleep mode. The active mode is triggered responsive to a trigger event, and the sleep mode may be triggered responsive to a sleep event. For example, and not by way of limitation, a sleep event may be the presence of at least one person inside the elevator car. When passengers are present in the elevator car <NUM>, the microphone <NUM> would pick up audio created by those passengers, and thus, some embodiments capture audio only when the elevator car <NUM> is empty. To this end, for instance, a motion sensor or other device for detecting presence may be in communication with the microphone <NUM>, or a motion sensor or other presence detector may be in communication with the controller <NUM>, which may communicate presence as needed to the microphone <NUM>. According to the claimed invention, a trigger event is the detection of no passengers present in the elevator car <NUM>, and thus, the microphone <NUM> may resume capturing sounds when the elevator car <NUM> is empty. Detection of a trigger event or a sleep event may be implemented in various ways, such as connecting a sensor of the trigger events and the sleep events to the processing unit <NUM> or to the controller <NUM>, either of which may activate or deactivate the microphone <NUM> as needed.

In some embodiments of this disclosure, both the vibration sensor <NUM> and the microphone <NUM> can operate at the same time, such that both vibrations and audio are measured simultaneously. As discussed above, both the vibration sensor <NUM> and the microphone <NUM> may be in communication with the processing unit <NUM>. Thus, if the monitoring system <NUM> includes a vibration sensor <NUM>, the processing unit <NUM> may receive a respective data stream from the vibration sensor <NUM>, and if the monitoring system <NUM> includes a microphone <NUM>, the processing unit <NUM> may receive a respective data stream from the microphone <NUM>.

The processing unit <NUM> may perform local preprocessing on each data stream received. For example, and not by way of limitation, the preprocessing may include one or more of the following: compression, removal of data within threshold values, or other operations. In some embodiments, preprocessing can reduce network traffic from the processing unit <NUM> to the cloud <NUM> or can reduce or eliminate data likely to not be useful to the analytics system <NUM>.

The processing unit <NUM> may transmit sensor data <NUM> to the cloud <NUM>, where sensor data <NUM> is the data received from the vibration sensor <NUM> or the microphone <NUM>, or both. As discussed above, the processing unit <NUM> may perform preprocessing on the data streams in some embodiments, and thus the sensor data <NUM> transmitted to the cloud <NUM> need not be raw data from the data streams but, rather, may be the data resulting from preprocessing the data streams. However, if preprocessing is not performed, then the sensor data <NUM> may be the same as the data streams received by the processing unit <NUM>. In some embodiments of this disclosure, the processing unit <NUM> transmits the sensor data <NUM> to the cloud <NUM> autonomously, for example, in real time, responsive to having received the data streams. Additionally or alternatively, the cloud <NUM> may request to receive the sensor data <NUM>, and the processing unit <NUM> may thus transmit the sensor data <NUM> on demand.

To enable transmission of the sensor data <NUM>, the processing unit <NUM> may be connected to the communication device <NUM>. The connection between the processing unit <NUM> and the communication device <NUM> may be wired or wireless, such as, for example, ethernet, optical, wireless fidelity (WiFi), Zigbee, Zwave, Bluetooth, or any other known communications protocol. For example, and not by way of limitation, the communication device <NUM> may be a cellular gateway or other device capable of communicating with the cloud <NUM>.

The cloud <NUM> may include one or more nodes, each of which may be a computing device or a portion of computing device. Through these nodes, the cloud <NUM> may execute an analytics system <NUM>, which may perform analytics on the sensor data <NUM> received from the processing unit <NUM>. Generally, the analytics system <NUM> may seek to determine the ride quality of the elevator system <NUM>, or the ride quality of the elevator system <NUM> and one or more nearby elevator systems <NUM>.

In some embodiments of this disclosure, the analytics system <NUM> utilizes machine learning to analyze the sensor data <NUM> received from the processing unit <NUM>. For instance, the analytics system <NUM> may include a cognitive engine that is trained on historical sensor data <NUM> associated with labels. This historical sensor data <NUM> may include data from the vibration sensor <NUM> or the microphone <NUM>, or both. Specifically, the labels may associate certain portions of the historical sensor data <NUM> with respective ride qualities, such as a specific levels of ride quality. For example, and not by way of limitation, if it is desired to group ride quality into three levels, then portions of the historical sensor data <NUM> may be labeled according to those three levels. After being trained, the cognitive engine may thus be capable of receiving sensor data <NUM> and determining ride quality of the received sensor data <NUM>. For example, given three levels of ride quality, the cognitive engine may be capable of identifying the ride quality level in each portion of sensor data <NUM>.

In some embodiments, the analytics system <NUM> automatically performs remedial actions responsive to various levels of ride quality that are less than an established minimum level. For example, and not by way of limitation, a remedial action may be issuance of an alert, which may notify an owner or maintenance organization of the elevator system <NUM> that maintenance is needed. For example, and not by way of limitation, if the analytics system <NUM> is capable of associating a portion of sensor data <NUM> with a quality level selected from a set of three quality levels, Level <NUM>, Level <NUM>, and Level <NUM>, where an increasing level number indicates increasing quality, then Level <NUM> may be considered the minimum acceptable level. In that case, a quality of Level <NUM> may cause the analytics system <NUM> to issue an alert indicating that maintenance may be needed, while a quality of Level <NUM> may cause the analytics system <NUM> to issue an alert that maintenance is urgently needed. Upon being notified of the alert, the maintenance organization can dispatch a technician to check the elevator system <NUM> in person. Thus, rather than determining ride quality only when a technician is present, as is conventionally the case, embodiments of this disclosure enable ride quality to be monitored continuously and remotely.

In some embodiments of this disclosure, analysis performed by the analytics system <NUM> may be facilitated by calibration. <FIG> illustrates calibration of the monitoring system <NUM>, according to some embodiments of this disclosure. As shown in <FIG>, in some embodiments, calibration of the monitoring system <NUM> is performed through the use of the vibration sensor <NUM> or the microphone <NUM>, or both, in conjunction with the conventional portable device <NUM> or other measurement device used manually. Although calibration is discussed as being performed with the portable device <NUM> herein, it will be understood that other measurement devices useable by a technician may be used during calibration as well. To perform calibration, the portable device <NUM> may be placed on the floor of the elevator car <NUM> as usual. Because use of the portable device <NUM> is well-known, there may exist established thresholds indicating acceptable measurements by the portable device.

During calibration, the portable device <NUM> may take measurements during movement of the elevator car <NUM>, while the vibration sensor <NUM> is also taking measurements or the microphone <NUM> is capturing audio, or both. Through techniques known in the art, one or more transformations may be established to map sensor data <NUM> of the vibration sensor <NUM> or the microphone <NUM>, or both, to measurements output by the portable device <NUM>. Specifically, for example, the sensor data <NUM> and the measurements of the portable device <NUM> may be transmitted to the cloud <NUM>, where the analytics system <NUM> may determine the one or more transformations. As such, because one or more acceptable ranges of measurements of the portable device <NUM> are known, it can be determined which measurements of the vibration sensor <NUM> or the microphone <NUM>, or both, represent an acceptable ride quality through the use of these one or more transformations.

Thus, in this manner, the monitoring system <NUM> may be trained offline. Further, in some embodiments, the analytics system <NUM> utilizes the resulting one or more transformations to analyze continuous ride quality remotely, based on current sensor data <NUM>.

<FIG> is a flow diagram of a method of monitoring continuous ride quality, according to some embodiments of this disclosure. It will be understood that this method <NUM> is an illustrative example and does not limit the various embodiments of this disclosure.

As shown in <FIG>, at block <NUM>, the monitoring system <NUM> is installed in an elevator system <NUM>. In some embodiments, this occurs during commissioning of the elevator system <NUM>, but alternatively, the monitoring system <NUM> may be installed in an elevator system <NUM> after the elevator system <NUM> has entered into regular use. As discussed above, the positioning of various components of the monitoring system <NUM> may vary.

At block <NUM>, the monitoring system <NUM> is initialized, which may include, for example, calibration or cognitive training. As discussed above, calibration may involve training the analytics system <NUM> to recognize various levels of ride quality by determining a transformation between measurements of the vibration sensor <NUM> or microphone <NUM> and measurements of the portable device <NUM>. Additionally or alternatively, the analytics system may learn, via machine learning, to recognize levels of ride quality in sensor data <NUM>.

At block <NUM>, the monitoring system <NUM> continuously detects at least one of vibration data and audio data. This may occur without manual supervision. Each of the vibration sensor <NUM> and the microphone <NUM> is associated with a respective set of trigger events, which cause them to begin detecting and generating a respective data stream, and may be associated with a respective set of sleep events, which cause them to stop detecting and thus stop generating a respective data stream.

At block <NUM>, the processing unit <NUM> of the monitoring system <NUM> receives a respective data stream from each of the vibration sensor <NUM> and the microphone <NUM>. At block <NUM>, the processing unit <NUM> preprocesses the data streams, which results in sensor data <NUM>. At block <NUM>, the processing unit <NUM> transmits the sensor data <NUM> through a communication device <NUM> to the cloud <NUM>. At block <NUM>, in the cloud, the analytics system <NUM> analyzes the sensor data <NUM> as it is received to thereby monitor the continuous ride quality remotely and in real time.

At decision block <NUM>, the analytics system <NUM> determines whether the sensor data <NUM> received meets a threshold quality. If the threshold quality is met, then at block <NUM>, the analytics system <NUM> continues receiving sensor data <NUM> and analyzing the sensor data <NUM> as it arrives. If the threshold quality is not met, however, then at block <NUM>, the analytics system <NUM> additionally issues an alert indicating that maintenance may be required. In either case, the analytics system <NUM> may continue to monitor the elevator system <NUM> by analyzing the sensor data <NUM> as it is received.

Thus, according to embodiments of this disclosure, ride quality of an elevator system <NUM> or group of elevator systems <NUM> can be monitored continuously and remotely, regardless of whether a technician is present. In some embodiments, this remote monitoring occurs in real time and can therefore be used to initiate maintenance visits on an as-needed basis.

As described above, embodiments can be in the form of processing unit-implemented processes and devices for practicing those processes, such as a processing unit. When implemented on a general-purpose microprocessing unit, the computer program code segments configure the microprocessing unit to create specific logic circuits.

Claim 1:
A monitoring system (<NUM>) comprising:
a vibration sensor (<NUM>) and/or microphone (<NUM>) configured to generate, at an elevator system (<NUM>), one or more data streams describing the ride of the elevator system (<NUM>) and comprising at least one of vibration data and audio data;
a communication device (<NUM>) configured to transmit sensor data based on the one or more data streams; and
an analytics system (<NUM>) remote from the elevator system (<NUM>), wherein the analytics system (<NUM>) is configured to receive the sensor data from the communication device (<NUM>) and to determine a ride quality of the elevator system (<NUM>), based on the sensor data,
characterized in that:
the vibration sensor (<NUM>) is in either a sleep mode or an active mode at a given time, such that the vibration sensor (<NUM>) measures vibrations during the active mode but not during the sleep mode, wherein the active mode is triggered in response to a first trigger event, the first trigger event being the presence of at least one person inside an elevator car (<NUM>) of the elevator system (<NUM>); and/or
the microphone (<NUM>) is in either a sleep mode or an active mode at a given time, such that the microphone (<NUM>) captures audio during the active mode but not during the sleep mode, wherein the active mode is triggered in response to a second trigger event, the second trigger event being the detection of no passengers present in the elevator car (<NUM>).