Within a Grow Room, it is common for swings in Relative Humidity and Temperature to occur, which can bring the room’s environmental parameters out of spec for a window of time during those oscillations. Determining the root cause of these swings can be beneficial to smoothing out the swings being seen and keeping the rooms within the desired environmental parameters for the specific phase in their growth cycle that they are in. Listed below is the thought process one should take to quickly isolate and minimize the swings in environmental data being seen:
- Validate sensor readings with a 3rd party sensor.
- Determine if there is a pattern to the swings in sensor data seen.
- Identify what devices are controlling the particular environmental parameter within the room.
- Confirm the sequence of operations used to maintain readings within the desired range of sensor data.
- Eliminate devices in the current sequence of operations to determine which devices have a larger impact on the environmental parameter (if there are multiple).
Validate Sensor Readings with a 3rd Party Sensor
The first step one should take when determining the source of swings in environmental data is to validate that the sensors reporting the swings are nominal. By checking the sensor readings with a third party hand-held sensor and testing the variance between the two sensors in the same area, one can confirm that the readings being provided by the sensors is nominal and also help determine if there is a micro-climate in the area surrounding the sensor that could be contributing to the swings in sensor data being observed.
Determine if There is a Pattern to the Swings in Sensor Data seen
Next, one would want to look at the historical data for the room to determine if there are any patterns that one can associate with the swings. For example, it is common to see decreases in humidity coupled with a decrease in room temperature if the HVAC units are heavily cooling the rooms. This in turn can result in swings in temperature and humidity depending on the desired temperature and humidity that the room is set to maintain with its equipment. Other common patterns one could see include swings in environmental parameters during the day but not during the night (due to heat and humidity load during the day-cycle) or swings in environmental parameters increasing through time due to an increase in heat and humidity load as the room nears the end of its growth cycle.
Identify What Devices are Controlling the Particular Environmental Parameter Within the Room
Once the sensor data has been examined for any potential patterns, the next step is to identify what outputs are controlling the particular environmental parameter. For Temperature swings, one should look at the device activity of HVAC cooling and heating stages, and for Relative Humidity swings one should look at the device activity of Dehumidifiers, Humidifiers, as well as the HVAC cooling and heating stages to determine if the swings are resulting from overlaps in activation of these devices.
Confirm the Sequence of Operations Used to Maintain Readings Within the Desired Range of Sensor Data
With the devices identified that are being used to control the environmental parameter being examined, one should next examine the rule logic being employed and setpoints being sent in order to isolate if there is any overlap that would result in two opposing mechanisms (such as a humidifier and dehumidifier for Relative Humidity) being active at the same time is resulting in the oscillations being observed. If an overlap is being seen between devices, setting a larger deadband between the activation of the two devices can help smooth out the oscillations being seen.
Eliminate Devices in the Current Sequence of Operations to Determine Which Devices Have a Larger Impact on the Environmental Parameter (if There are Multiple).
With all of the data collected thus far on identifying the swings in environmental parameters, determining a pattern in the data, and cross-referencing device data to determine any overlaps in device activation, the last remaining piece to isolate is the role that individual devices play in the swings in environmental data seen.
By removing devices from the sequence of operations, one can determine the primary or secondary effects of those device activations on the room’s environmental parameters. For example, If one has an HVAC units with multiple stages of cooling, one could prevent the second stage of the HVAC unit’s cooling from activating in order to determine if the second stage of the HVAC unit turning on is resulting on the room rapidly cooling and resulting in swings in both temperature and humidity. Similarly, if one has multiple banks of dehumidifiers, one can stage the dehumidifiers such that only a few dehumidifiers turn on instead of all of the dehumidifiers at once in order to isolate if the combined throughput of the dehumidifiers result in overshooting the desired humidity range for the room. Lastly, for rooms that have a passive humidity load, one could turn off the humidifiers within the room to isolate if swings in Relative Humidity are due to a combination of over-dehumidification coupled with the humidifiers overshooting the desired Relative Humidity Range within the room.
By following the steps outlined above one can verify the oscillations in environmental parameters are an actual occurrence, determine any pattern with the sensor data seen, identify what devices are controlling that parameter directly, and isolate which devices are the primary and secondary drivers that result in the change in environmental parameters through time.