从 MT2-AM8 模拟量模块迁移到 Easy521 PLC（Modbus TCP）
- 读取 D700（阀后流量）、D710（阀后压力）、D720（阀前压力）， 读用功能码 03，0~32000 线性映射到各自量程（300 SLM / 400 kPa / 300 kPa） - 输出 D730（电机位置，0~10V），写用功能码 06，行程仍为 0~1000、死区 800 - 复用 MT2 骨架，保留 get_flow/get_pressure/set_motor_position 接口， channel 参数改为直接 Modbus 地址 - config.py 新增 PLC 设置，保留 MT2AM8 设置为死代码（MT2AM8Client 类保留） - 同步更新 README.md 中的硬件接线、配置默认值与模块职责描述
This commit is contained in:
+88
-25
@@ -22,6 +22,37 @@ def _close(a, b, rel=1e-6):
|
||||
return abs(a - b) <= rel * max(1.0, abs(a), abs(b))
|
||||
|
||||
|
||||
def _write_sweep_csv(path, *, scale=1.0, visit_openings=(100.0, 50.0, 0.0)):
|
||||
"""构造合成扫点 CSV：每个 step 30 个采样点，全程稳态。
|
||||
|
||||
``visit_openings`` 为开度的访问顺序（模拟 open_loop.py 的打乱顺序）；
|
||||
A_eff 真值 = scale * (1000 - x) / 400，Q_ss 按阻塞流（F=1）反推。
|
||||
"""
|
||||
rows = []
|
||||
for step, opening in enumerate(visit_openings):
|
||||
x = 1000.0 - opening / 100.0 * 200.0 # 与 flow_control 的映射一致
|
||||
a_eff = scale * (1000.0 - x) / 400.0 # 单调递减的真值
|
||||
q_ss = a_eff * (400.0 + P_ATM) # 阻塞流，F=1
|
||||
for i in range(30):
|
||||
rows.append({
|
||||
"time_s": f"{step * 10 + i * 0.1:.6f}",
|
||||
"step_index": step,
|
||||
"opening_pct": opening,
|
||||
"motor_position": x,
|
||||
"flow_before_slm": "",
|
||||
"flow_after_slm": q_ss,
|
||||
"pressure_before_kpa": 400.0,
|
||||
"pressure_after_kpa": 0.0,
|
||||
"P_abs_ratio": "",
|
||||
"is_ratio_smaller_than_0.528": "Y",
|
||||
})
|
||||
|
||||
with path.open("w", newline="", encoding="utf-8-sig") as f:
|
||||
writer = csv.DictWriter(f, fieldnames=list(rows[0].keys()))
|
||||
writer.writeheader()
|
||||
writer.writerows(rows)
|
||||
|
||||
|
||||
def test_f_ratio():
|
||||
assert f_ratio(0.4) == 1.0
|
||||
assert f_ratio(CRITICAL_RATIO) == 1.0
|
||||
@@ -70,46 +101,75 @@ def test_non_monotonic_raises():
|
||||
def test_identify_end_to_end():
|
||||
import identify_valve
|
||||
|
||||
# 构造合成扫点 CSV：每个 step 30 个采样点，全程稳态。
|
||||
rows = []
|
||||
for step, x in enumerate((800.0, 900.0, 1000.0)):
|
||||
a_eff = (1000.0 - x) / 400.0 # 单调递减的真值
|
||||
q_ss = a_eff * (400.0 + P_ATM) # 阻塞流，F=1
|
||||
for i in range(30):
|
||||
rows.append({
|
||||
"time_s": f"{step * 10 + i * 0.1:.6f}",
|
||||
"step_index": step,
|
||||
"opening_pct": 100.0 - step * 50.0,
|
||||
"motor_position": x,
|
||||
"flow_before_slm": "",
|
||||
"flow_after_slm": q_ss,
|
||||
"pressure_before_kpa": 400.0,
|
||||
"pressure_after_kpa": 0.0,
|
||||
"P_abs_ratio": "",
|
||||
"is_ratio_smaller_than_0.528": "Y",
|
||||
})
|
||||
|
||||
with tempfile.TemporaryDirectory() as tmp:
|
||||
csv_path = Path(tmp) / "sweep.csv"
|
||||
out_path = Path(tmp) / "model.json"
|
||||
with csv_path.open("w", newline="", encoding="utf-8-sig") as f:
|
||||
writer = csv.DictWriter(f, fieldnames=list(rows[0].keys()))
|
||||
writer.writeheader()
|
||||
writer.writerows(rows)
|
||||
_write_sweep_csv(csv_path)
|
||||
|
||||
model, steady, table, dropped, stats = identify_valve.identify(
|
||||
csv_path, tail=20, out_path=str(out_path)
|
||||
model, steady, table, dropped, stats, area_points = identify_valve.identify(
|
||||
[csv_path], tail=20, out_path=str(out_path)
|
||||
)
|
||||
assert len(table) == 3, table
|
||||
assert stats["choked"] == 3
|
||||
assert not dropped
|
||||
for x, a in table:
|
||||
assert _close(a, (1000.0 - x) / 400.0, rel=0.01), (x, a)
|
||||
assert len(area_points) == 3
|
||||
|
||||
loaded = ValveModel.load(str(out_path), 800.0, 1000.0)
|
||||
assert _close(loaded.area_from_stroke(900.0), 0.25, rel=0.01)
|
||||
|
||||
|
||||
def test_merge_multiple_csvs():
|
||||
import identify_valve
|
||||
|
||||
with tempfile.TemporaryDirectory() as tmp:
|
||||
csv_a = Path(tmp) / "run_a.csv"
|
||||
csv_b = Path(tmp) / "run_b.csv"
|
||||
_write_sweep_csv(csv_a, scale=1.0)
|
||||
_write_sweep_csv(csv_b, scale=1.1)
|
||||
|
||||
model, steady, table, dropped, stats, _ = identify_valve.identify(
|
||||
[csv_a, csv_b], tail=20
|
||||
)
|
||||
assert len(steady) == 6, steady
|
||||
assert stats["choked"] == 6
|
||||
assert not dropped
|
||||
# 同一行程的两个点先平均：A_eff = 1.05 * 真值
|
||||
for x, a in table:
|
||||
assert _close(a, 1.05 * (1000.0 - x) / 400.0, rel=0.01), (x, a)
|
||||
|
||||
|
||||
def test_direction_tagging():
|
||||
import identify_valve
|
||||
|
||||
with tempfile.TemporaryDirectory() as tmp:
|
||||
csv_path = Path(tmp) / "shuffled.csv"
|
||||
_write_sweep_csv(csv_path, visit_openings=(0.0, 100.0, 50.0))
|
||||
points = identify_valve.load_steady_points(csv_path, tail=20)
|
||||
directions = [p[4] for p in points]
|
||||
assert directions == [None, "up", "down"], directions
|
||||
|
||||
|
||||
def test_resolve_csv_paths_glob():
|
||||
import identify_valve
|
||||
|
||||
with tempfile.TemporaryDirectory() as tmp:
|
||||
base = Path(tmp)
|
||||
(base / "b.csv").write_text("", encoding="utf-8")
|
||||
(base / "a.csv").write_text("", encoding="utf-8")
|
||||
(base / "c.txt").write_text("", encoding="utf-8")
|
||||
|
||||
# glob 展开并按名称排序，只匹配 CSV
|
||||
paths = identify_valve.resolve_csv_paths([str(base / "*.csv")])
|
||||
assert [Path(p).name for p in paths] == ["a.csv", "b.csv"], paths
|
||||
# 显式路径 + glob 混用时去重
|
||||
paths = identify_valve.resolve_csv_paths(
|
||||
[str(base / "*.csv"), str(base / "a.csv")]
|
||||
)
|
||||
assert [Path(p).name for p in paths] == ["a.csv", "b.csv"], paths
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
tests = [
|
||||
test_f_ratio,
|
||||
@@ -117,6 +177,9 @@ if __name__ == "__main__":
|
||||
test_valve_model_roundtrip,
|
||||
test_non_monotonic_raises,
|
||||
test_identify_end_to_end,
|
||||
test_merge_multiple_csvs,
|
||||
test_direction_tagging,
|
||||
test_resolve_csv_paths_glob,
|
||||
]
|
||||
for test in tests:
|
||||
test()
|
||||
|
||||
Reference in New Issue
Block a user