esphome:
name: gewicht-sensor2
esp8266:
board: d1_mini
globals:
- id: initial_zero
type: float
restore_value: yes
# NOTE: make sure to align this value to the one used in "calibrate_linear" below!
initial_value: '-167963'
- id: auto_tare_enabled
type: bool
restore_value: yes
initial_value: 'true'
- id: auto_tare_difference
type: float
restore_value: yes
initial_value: '0'
# Enable logging
logger:
# Enable Web server.
web_server:
port: 80
# Enable Home Assistant API
api:
encryption:
key: "TF8XhBQyGQchHOaL8HSZSp1SXFeS38wwO7r3w9t4AqM="
ota:
password: "263582af572ea3564059022dad6b3e27"
wifi:
ssid: wifi-name
password: whatsthepassword
# Enable fallback hotspot (captive portal) in case wifi connection fails
ap:
ssid: "Gewicht-Sensor2 Fallback Hotspot"
password: "whatsthepassword"
captive_portal:
#sensor:
# - platform: hx711
# name: "HX711 Value"
# dout_pin: D1
# clk_pin: D2
# gain: 128
# update_interval: 1s
button:
## Button used to initiate a manual tare
- platform: template
id: smart_scale_manual_tare_action_switch
name: "Smart Scale Manual Tare Action"
icon: mdi:scale-balance
on_press:
- lambda: |-
id(auto_tare_difference) = id(initial_zero) - id(smart_scale_hx711_value_raw).state;
switch:
## Switch to enable/disable the auto tare feature
- platform: template
id: smart_scale_continuous_tare_enabled
name: "Smart Scale Continuous Tare Enabled"
lambda: |-
return id(auto_tare_enabled);
turn_on_action:
- lambda: |-
id(auto_tare_enabled) = true;
turn_off_action:
- lambda: |-
id(auto_tare_enabled) = false;
## Sensor Configuration ##
sensor:
# template sensors from global variables
- platform: template
id: smart_scale_initial_zero
name: "Smart Scale Initial Zero"
lambda: |-
return id(initial_zero);
update_interval: 1s
- platform: template
id: smart_scale_auto_tare_difference
name: "Smart Scale Auto Tare Difference"
lambda: |-
return id(auto_tare_difference);
update_interval: 1s
# sensors imported from home assistant
- platform: homeassistant
id: homeassistant_initial_zero
entity_id: input_number.smart_scale_initial_zero
on_value:
then:
- lambda: |-
id(initial_zero) = x;
# RAW Scale input
- platform: hx711
id: smart_scale_hx711_value_raw
internal: True
dout_pin: D1
clk_pin: D2
gain: 128
unit_of_measurement: kg
accuracy_decimals: 3
update_interval: 15s
filters:
- sliding_window_moving_average:
window_size: 3
send_every: 1
on_value:
then:
- sensor.template.publish:
id: smart_scale_hx711_value
state: !lambda 'return id(smart_scale_hx711_value_raw).state;'
- if:
condition:
and:
- lambda: 'return id(auto_tare_enabled);'
# current smart scale value is below approx. 10KG (raw value -275743) aka nobody is standing on the scale
- lambda: 'return id(smart_scale_hx711_value).state < 10.0;'
then:
- if:
condition:
# current raw scale value is below expected zero value
- lambda: 'return id(smart_scale_hx711_value_raw).state < (id(initial_zero) - id(auto_tare_difference));'
then:
# INcrease Auto-Tare offset to slowly align real zero value with expected zero value
- lambda: |-
id(auto_tare_difference) += 10;
else:
# DEcrease Auto-Tare offset to slowly align real zero value with expected zero value
- lambda: |-
id(auto_tare_difference) -= 10;
# Mapped value to KG
- platform: template
id: smart_scale_hx711_value
name: "Smart Scale HX711 Value"
internal: False
filters:
# apply auto_tare difference
- lambda: 'return x + id(auto_tare_difference);'
# apply rough calibration
- calibrate_linear:
# retrieve these values by evaluating the raw values with loads of known mass.
# note that a bigger difference between measurements usually results in higher resolution,
# so measure 0 Kg and the highest known mass you have (like f.ex. your own weight, measured by a normal scale with good accuracy)
- -167963 -> 0
- 46143 -> 77.6
# map values below 0.1 to 0 (to decrease value changes due to random fluctuation)
- lambda: |-
if (x <= 0.1) {
return 0.0;
} else {
return x;
}
unit_of_measurement: kg
accuracy_decimals: 2
update_interval: 2s
ESPHome location to sensor information: https://esphome.io/components/sensor/hx711.html